mirror of
https://github.com/explosion/spaCy.git
synced 2024-12-24 17:06:29 +03:00
Merge pull request #5788 from explosion/master-tmp
This commit is contained in:
Ines Montani
GitHub
commit
311d0bde29
106
.github/contributors/PluieElectrique.md
vendored
Normal file
106
.github/contributors/PluieElectrique.md
vendored
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
# spaCy contributor agreement
|
||||
|
||||
This spaCy Contributor Agreement (**"SCA"**) is based on the
|
||||
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
|
||||
The SCA applies to any contribution that you make to any product or project
|
||||
managed by us (the **"project"**), and sets out the intellectual property rights
|
||||
you grant to us in the contributed materials. The term **"us"** shall mean
|
||||
[ExplosionAI GmbH](https://explosion.ai/legal). The term
|
||||
**"you"** shall mean the person or entity identified below.
|
||||
|
||||
If you agree to be bound by these terms, fill in the information requested
|
||||
below and include the filled-in version with your first pull request, under the
|
||||
folder [`.github/contributors/`](/.github/contributors/). The name of the file
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
example_user would create the file `.github/contributors/example_user.md`.
|
||||
|
||||
Read this agreement carefully before signing. These terms and conditions
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [X] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect to my
|
||||
contributions.
|
||||
|
||||
* [ ] I am signing on behalf of my employer or a legal entity and I have the
|
||||
actual authority to contractually bind that entity.
|
||||
|
||||
## Contributor Details
|
||||
|
||||
| Field | Entry |
|
||||
|------------------------------- | -------------------- |
|
||||
| Name | Pluie |
|
||||
| Company name (if applicable) | |
|
||||
| Title or role (if applicable) | |
|
||||
| Date | 2020-06-18 |
|
||||
| GitHub username | PluieElectrique |
|
||||
| Website (optional) | |
|
||||
106
.github/contributors/abchapman93.md
vendored
Normal file
106
.github/contributors/abchapman93.md
vendored
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
# spaCy contributor agreement
|
||||
|
||||
This spaCy Contributor Agreement (**"SCA"**) is based on the
|
||||
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
|
||||
The SCA applies to any contribution that you make to any product or project
|
||||
managed by us (the **"project"**), and sets out the intellectual property rights
|
||||
you grant to us in the contributed materials. The term **"us"** shall mean
|
||||
[ExplosionAI GmbH](https://explosion.ai/legal). The term
|
||||
**"you"** shall mean the person or entity identified below.
|
||||
|
||||
If you agree to be bound by these terms, fill in the information requested
|
||||
below and include the filled-in version with your first pull request, under the
|
||||
folder [`.github/contributors/`](/.github/contributors/). The name of the file
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
example_user would create the file `.github/contributors/example_user.md`.
|
||||
|
||||
Read this agreement carefully before signing. These terms and conditions
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [X] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect to my
|
||||
contributions.
|
||||
|
||||
* [ ] I am signing on behalf of my employer or a legal entity and I have the
|
||||
actual authority to contractually bind that entity.
|
||||
|
||||
## Contributor Details
|
||||
|
||||
| Field | Entry |
|
||||
|------------------------------- | -------------------- |
|
||||
| Name | Alec Chapman |
|
||||
| Company name (if applicable) | |
|
||||
| Title or role (if applicable) | |
|
||||
| Date | 7/17/2020 |
|
||||
| GitHub username | abchapman93 |
|
||||
| Website (optional) | |
|
||||
106
.github/contributors/gandersen101.md
vendored
Normal file
106
.github/contributors/gandersen101.md
vendored
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
# spaCy contributor agreement
|
||||
|
||||
This spaCy Contributor Agreement (**"SCA"**) is based on the
|
||||
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
|
||||
The SCA applies to any contribution that you make to any product or project
|
||||
managed by us (the **"project"**), and sets out the intellectual property rights
|
||||
you grant to us in the contributed materials. The term **"us"** shall mean
|
||||
[ExplosionAI GmbH](https://explosion.ai/legal). The term
|
||||
**"you"** shall mean the person or entity identified below.
|
||||
|
||||
If you agree to be bound by these terms, fill in the information requested
|
||||
below and include the filled-in version with your first pull request, under the
|
||||
folder [`.github/contributors/`](/.github/contributors/). The name of the file
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
example_user would create the file `.github/contributors/example_user.md`.
|
||||
|
||||
Read this agreement carefully before signing. These terms and conditions
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [ x] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect to my
|
||||
contributions.
|
||||
|
||||
* [ ] I am signing on behalf of my employer or a legal entity and I have the
|
||||
actual authority to contractually bind that entity.
|
||||
|
||||
## Contributor Details
|
||||
|
||||
| Field | Entry |
|
||||
|------------------------------- | -------------------- |
|
||||
| Name | Grant Andersen |
|
||||
| Company name (if applicable) | |
|
||||
| Title or role (if applicable) | |
|
||||
| Date | 07.06.2020 |
|
||||
| GitHub username | gandersen101 |
|
||||
| Website (optional) | |
|
||||
106
.github/contributors/jbesomi.md
vendored
Normal file
106
.github/contributors/jbesomi.md
vendored
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
# spaCy contributor agreement
|
||||
|
||||
This spaCy Contributor Agreement (**"SCA"**) is based on the
|
||||
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
|
||||
The SCA applies to any contribution that you make to any product or project
|
||||
managed by us (the **"project"**), and sets out the intellectual property rights
|
||||
you grant to us in the contributed materials. The term **"us"** shall mean
|
||||
[ExplosionAI GmbH](https://explosion.ai/legal). The term
|
||||
**"you"** shall mean the person or entity identified below.
|
||||
|
||||
If you agree to be bound by these terms, fill in the information requested
|
||||
below and include the filled-in version with your first pull request, under the
|
||||
folder [`.github/contributors/`](/.github/contributors/). The name of the file
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
example_user would create the file `.github/contributors/example_user.md`.
|
||||
|
||||
Read this agreement carefully before signing. These terms and conditions
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [x] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect to my
|
||||
contributions.
|
||||
|
||||
* [ ] I am signing on behalf of my employer or a legal entity and I have the
|
||||
actual authority to contractually bind that entity.
|
||||
|
||||
## Contributor Details
|
||||
|
||||
| Field | Entry |
|
||||
|------------------------------- | -------------------- |
|
||||
| Name | Jonathan B. |
|
||||
| Company name (if applicable) | besomi.ai |
|
||||
| Title or role (if applicable) | - |
|
||||
| Date | 07.07.2020 |
|
||||
| GitHub username | jbesomi |
|
||||
| Website (optional) | besomi.ai |
|
||||
106
.github/contributors/mikeizbicki.md
vendored
Normal file
106
.github/contributors/mikeizbicki.md
vendored
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
# spaCy contributor agreement
|
||||
|
||||
This spaCy Contributor Agreement (**"SCA"**) is based on the
|
||||
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
|
||||
The SCA applies to any contribution that you make to any product or project
|
||||
managed by us (the **"project"**), and sets out the intellectual property rights
|
||||
you grant to us in the contributed materials. The term **"us"** shall mean
|
||||
[ExplosionAI GmbH](https://explosion.ai/legal). The term
|
||||
**"you"** shall mean the person or entity identified below.
|
||||
|
||||
If you agree to be bound by these terms, fill in the information requested
|
||||
below and include the filled-in version with your first pull request, under the
|
||||
folder [`.github/contributors/`](/.github/contributors/). The name of the file
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
example_user would create the file `.github/contributors/example_user.md`.
|
||||
|
||||
Read this agreement carefully before signing. These terms and conditions
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [x] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect to my
|
||||
contributions.
|
||||
|
||||
* [ ] I am signing on behalf of my employer or a legal entity and I have the
|
||||
actual authority to contractually bind that entity.
|
||||
|
||||
## Contributor Details
|
||||
|
||||
| Field | Entry |
|
||||
|------------------------------- | -------------------- |
|
||||
| Name | Mike Izbicki |
|
||||
| Company name (if applicable) | |
|
||||
| Title or role (if applicable) | |
|
||||
| Date | 02 Jun 2020 |
|
||||
| GitHub username | mikeizbicki |
|
||||
| Website (optional) | https://izbicki.me |
|
||||
106
.github/contributors/rameshhpathak.md
vendored
Normal file
106
.github/contributors/rameshhpathak.md
vendored
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
# spaCy contributor agreement
|
||||
|
||||
This spaCy Contributor Agreement (**"SCA"**) is based on the
|
||||
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
|
||||
The SCA applies to any contribution that you make to any product or project
|
||||
managed by us (the **"project"**), and sets out the intellectual property rights
|
||||
you grant to us in the contributed materials. The term **"us"** shall mean
|
||||
[ExplosionAI GmbH](https://explosion.ai/legal). The term
|
||||
**"you"** shall mean the person or entity identified below.
|
||||
|
||||
If you agree to be bound by these terms, fill in the information requested
|
||||
below and include the filled-in version with your first pull request, under the
|
||||
folder [`.github/contributors/`](/.github/contributors/). The name of the file
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
example_user would create the file `.github/contributors/example_user.md`.
|
||||
|
||||
Read this agreement carefully before signing. These terms and conditions
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [x] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect to my
|
||||
contributions.
|
||||
|
||||
* [ ] I am signing on behalf of my employer or a legal entity and I have the
|
||||
actual authority to contractually bind that entity.
|
||||
|
||||
## Contributor Details
|
||||
|
||||
| Field | Entry |
|
||||
|------------------------------- | -------------------- |
|
||||
| Name | Ramesh Pathak |
|
||||
| Company name (if applicable) | Diyo AI |
|
||||
| Title or role (if applicable) | AI Engineer |
|
||||
| Date | June 21, 2020 |
|
||||
| GitHub username | rameshhpathak |
|
||||
| Website (optional) |rameshhpathak.github.io| |
|
||||
106
.github/contributors/richardliaw.md
vendored
Normal file
106
.github/contributors/richardliaw.md
vendored
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
# spaCy contributor agreement
|
||||
|
||||
This spaCy Contributor Agreement (**"SCA"**) is based on the
|
||||
[Oracle Contributor Agreement](http://www.oracle.com/technetwork/oca-405177.pdf).
|
||||
The SCA applies to any contribution that you make to any product or project
|
||||
managed by us (the **"project"**), and sets out the intellectual property rights
|
||||
you grant to us in the contributed materials. The term **"us"** shall mean
|
||||
[ExplosionAI GmbH](https://explosion.ai/legal). The term
|
||||
**"you"** shall mean the person or entity identified below.
|
||||
|
||||
If you agree to be bound by these terms, fill in the information requested
|
||||
below and include the filled-in version with your first pull request, under the
|
||||
folder [`.github/contributors/`](/.github/contributors/). The name of the file
|
||||
should be your GitHub username, with the extension `.md`. For example, the user
|
||||
example_user would create the file `.github/contributors/example_user.md`.
|
||||
|
||||
Read this agreement carefully before signing. These terms and conditions
|
||||
constitute a binding legal agreement.
|
||||
|
||||
## Contributor Agreement
|
||||
|
||||
1. The term "contribution" or "contributed materials" means any source code,
|
||||
object code, patch, tool, sample, graphic, specification, manual,
|
||||
documentation, or any other material posted or submitted by you to the project.
|
||||
|
||||
2. With respect to any worldwide copyrights, or copyright applications and
|
||||
registrations, in your contribution:
|
||||
|
||||
* you hereby assign to us joint ownership, and to the extent that such
|
||||
assignment is or becomes invalid, ineffective or unenforceable, you hereby
|
||||
grant to us a perpetual, irrevocable, non-exclusive, worldwide, no-charge,
|
||||
royalty-free, unrestricted license to exercise all rights under those
|
||||
copyrights. This includes, at our option, the right to sublicense these same
|
||||
rights to third parties through multiple levels of sublicensees or other
|
||||
licensing arrangements;
|
||||
|
||||
* you agree that each of us can do all things in relation to your
|
||||
contribution as if each of us were the sole owners, and if one of us makes
|
||||
a derivative work of your contribution, the one who makes the derivative
|
||||
work (or has it made will be the sole owner of that derivative work;
|
||||
|
||||
* you agree that you will not assert any moral rights in your contribution
|
||||
against us, our licensees or transferees;
|
||||
|
||||
* you agree that we may register a copyright in your contribution and
|
||||
exercise all ownership rights associated with it; and
|
||||
|
||||
* you agree that neither of us has any duty to consult with, obtain the
|
||||
consent of, pay or render an accounting to the other for any use or
|
||||
distribution of your contribution.
|
||||
|
||||
3. With respect to any patents you own, or that you can license without payment
|
||||
to any third party, you hereby grant to us a perpetual, irrevocable,
|
||||
non-exclusive, worldwide, no-charge, royalty-free license to:
|
||||
|
||||
* make, have made, use, sell, offer to sell, import, and otherwise transfer
|
||||
your contribution in whole or in part, alone or in combination with or
|
||||
included in any product, work or materials arising out of the project to
|
||||
which your contribution was submitted, and
|
||||
|
||||
* at our option, to sublicense these same rights to third parties through
|
||||
multiple levels of sublicensees or other licensing arrangements.
|
||||
|
||||
4. Except as set out above, you keep all right, title, and interest in your
|
||||
contribution. The rights that you grant to us under these terms are effective
|
||||
on the date you first submitted a contribution to us, even if your submission
|
||||
took place before the date you sign these terms.
|
||||
|
||||
5. You covenant, represent, warrant and agree that:
|
||||
|
||||
* Each contribution that you submit is and shall be an original work of
|
||||
authorship and you can legally grant the rights set out in this SCA;
|
||||
|
||||
* to the best of your knowledge, each contribution will not violate any
|
||||
third party's copyrights, trademarks, patents, or other intellectual
|
||||
property rights; and
|
||||
|
||||
* each contribution shall be in compliance with U.S. export control laws and
|
||||
other applicable export and import laws. You agree to notify us if you
|
||||
become aware of any circumstance which would make any of the foregoing
|
||||
representations inaccurate in any respect. We may publicly disclose your
|
||||
participation in the project, including the fact that you have signed the SCA.
|
||||
|
||||
6. This SCA is governed by the laws of the State of California and applicable
|
||||
U.S. Federal law. Any choice of law rules will not apply.
|
||||
|
||||
7. Please place an “x” on one of the applicable statement below. Please do NOT
|
||||
mark both statements:
|
||||
|
||||
* [x] I am signing on behalf of myself as an individual and no other person
|
||||
or entity, including my employer, has or will have rights with respect to my
|
||||
contributions.
|
||||
|
||||
* [ ] I am signing on behalf of my employer or a legal entity and I have the
|
||||
actual authority to contractually bind that entity.
|
||||
|
||||
## Contributor Details
|
||||
|
||||
| Field | Entry |
|
||||
|------------------------------- | -------------------- |
|
||||
| Name | Richard Liaw |
|
||||
| Company name (if applicable) | |
|
||||
| Title or role (if applicable) | |
|
||||
| Date | 06/22/2020 |
|
||||
| GitHub username | richardliaw |
|
||||
| Website (optional) | |
|
||||
1
.gitignore
vendored
1
.gitignore
vendored
|
|
@ -71,6 +71,7 @@ Pipfile.lock
|
|||
*.egg
|
||||
.eggs
|
||||
MANIFEST
|
||||
spacy/git_info.py
|
||||
|
||||
# Temporary files
|
||||
*.~*
|
||||
|
|
|
|||
|
|
@ -5,3 +5,4 @@ include README.md
|
|||
include pyproject.toml
|
||||
recursive-exclude spacy/lang *.json
|
||||
recursive-include spacy/lang *.json.gz
|
||||
recursive-include licenses *
|
||||
|
|
|
|||
4
Makefile
4
Makefile
|
|
@ -5,7 +5,7 @@ VENV := ./env$(PYVER)
|
|||
version := $(shell "bin/get-version.sh")
|
||||
|
||||
dist/spacy-$(version).pex : wheelhouse/spacy-$(version).stamp
|
||||
$(VENV)/bin/pex -f ./wheelhouse --no-index --disable-cache -m spacy -o $@ spacy==$(version) spacy-lookups-data jieba pkuseg==0.0.22 sudachipy sudachidict_core
|
||||
$(VENV)/bin/pex -f ./wheelhouse --no-index --disable-cache -m spacy -o $@ spacy==$(version) spacy-lookups-data jieba pkuseg==0.0.25 sudachipy sudachidict_core
|
||||
chmod a+rx $@
|
||||
cp $@ dist/spacy.pex
|
||||
|
||||
|
|
@ -15,7 +15,7 @@ dist/pytest.pex : wheelhouse/pytest-*.whl
|
|||
|
||||
wheelhouse/spacy-$(version).stamp : $(VENV)/bin/pex setup.py spacy/*.py* spacy/*/*.py*
|
||||
$(VENV)/bin/pip wheel . -w ./wheelhouse
|
||||
$(VENV)/bin/pip wheel spacy-lookups-data jieba pkuseg==0.0.22 sudachipy sudachidict_core -w ./wheelhouse
|
||||
$(VENV)/bin/pip wheel spacy-lookups-data jieba pkuseg==0.0.25 sudachipy sudachidict_core -w ./wheelhouse
|
||||
touch $@
|
||||
|
||||
wheelhouse/pytest-%.whl : $(VENV)/bin/pex
|
||||
|
|
|
|||
|
|
@ -16,8 +16,6 @@ from __future__ import unicode_literals, print_function
|
|||
import plac
|
||||
import random
|
||||
from pathlib import Path
|
||||
|
||||
from spacy.vocab import Vocab
|
||||
import spacy
|
||||
from spacy.kb import KnowledgeBase
|
||||
|
||||
|
|
@ -61,13 +59,13 @@ TRAIN_DATA = sample_train_data()
|
|||
output_dir=("Optional output directory", "option", "o", Path),
|
||||
n_iter=("Number of training iterations", "option", "n", int),
|
||||
)
|
||||
def main(kb_path, vocab_path=None, output_dir=None, n_iter=50):
|
||||
def main(kb_path, vocab_path, output_dir=None, n_iter=50):
|
||||
"""Create a blank model with the specified vocab, set up the pipeline and train the entity linker.
|
||||
The `vocab` should be the one used during creation of the KB."""
|
||||
vocab = Vocab().from_disk(vocab_path)
|
||||
# create blank English model with correct vocab
|
||||
nlp = spacy.blank("en", vocab=vocab)
|
||||
nlp.vocab.vectors.name = "nel_vectors"
|
||||
nlp = spacy.blank("en")
|
||||
nlp.vocab.from_disk(vocab_path)
|
||||
nlp.vocab.vectors.name = "spacy_pretrained_vectors"
|
||||
print("Created blank 'en' model with vocab from '%s'" % vocab_path)
|
||||
|
||||
# Add a sentencizer component. Alternatively, add a dependency parser for higher accuracy.
|
||||
|
|
@ -96,7 +94,7 @@ def main(kb_path, vocab_path=None, output_dir=None, n_iter=50):
|
|||
# Convert the texts to docs to make sure we have doc.ents set for the training examples.
|
||||
# Also ensure that the annotated examples correspond to known identifiers in the knowledge base.
|
||||
kb_ids = nlp.get_pipe("entity_linker").kb.get_entity_strings()
|
||||
train_examples = []
|
||||
train_examples = []
|
||||
for text, annotation in TRAIN_DATA:
|
||||
with nlp.select_pipes(disable="entity_linker"):
|
||||
doc = nlp(text)
|
||||
|
|
@ -111,7 +109,7 @@ def main(kb_path, vocab_path=None, output_dir=None, n_iter=50):
|
|||
"Removed", kb_id, "from training because it is not in the KB."
|
||||
)
|
||||
annotation_clean["links"][offset] = new_dict
|
||||
train_examples .append(Example.from_dict(doc, annotation_clean))
|
||||
train_examples.append(Example.from_dict(doc, annotation_clean))
|
||||
|
||||
with nlp.select_pipes(enable="entity_linker"): # only train entity linker
|
||||
# reset and initialize the weights randomly
|
||||
|
|
|
|||
52
setup.py
52
setup.py
|
|
@ -4,13 +4,14 @@ import sys
|
|||
import platform
|
||||
from distutils.command.build_ext import build_ext
|
||||
from distutils.sysconfig import get_python_inc
|
||||
import distutils.util
|
||||
from distutils import ccompiler, msvccompiler
|
||||
import numpy
|
||||
from pathlib import Path
|
||||
import shutil
|
||||
from Cython.Build import cythonize
|
||||
from Cython.Compiler import Options
|
||||
import os
|
||||
import subprocess
|
||||
|
||||
|
||||
ROOT = Path(__file__).parent
|
||||
|
|
@ -75,7 +76,6 @@ COPY_FILES = {
|
|||
|
||||
def is_new_osx():
|
||||
"""Check whether we're on OSX >= 10.7"""
|
||||
name = distutils.util.get_platform()
|
||||
if sys.platform != "darwin":
|
||||
return False
|
||||
mac_ver = platform.mac_ver()[0]
|
||||
|
|
@ -118,6 +118,53 @@ class build_ext_subclass(build_ext, build_ext_options):
|
|||
build_ext.build_extensions(self)
|
||||
|
||||
|
||||
# Include the git version in the build (adapted from NumPy)
|
||||
# Copyright (c) 2005-2020, NumPy Developers.
|
||||
# BSD 3-Clause license, see licenses/3rd_party_licenses.txt
|
||||
def write_git_info_py(filename="spacy/git_info.py"):
|
||||
def _minimal_ext_cmd(cmd):
|
||||
# construct minimal environment
|
||||
env = {}
|
||||
for k in ["SYSTEMROOT", "PATH", "HOME"]:
|
||||
v = os.environ.get(k)
|
||||
if v is not None:
|
||||
env[k] = v
|
||||
# LANGUAGE is used on win32
|
||||
env["LANGUAGE"] = "C"
|
||||
env["LANG"] = "C"
|
||||
env["LC_ALL"] = "C"
|
||||
out = subprocess.check_output(cmd, stderr=subprocess.STDOUT, env=env)
|
||||
return out
|
||||
|
||||
git_version = "Unknown"
|
||||
if Path(".git").exists():
|
||||
try:
|
||||
out = _minimal_ext_cmd(["git", "rev-parse", "--short", "HEAD"])
|
||||
git_version = out.strip().decode("ascii")
|
||||
except Exception:
|
||||
pass
|
||||
elif Path(filename).exists():
|
||||
# must be a source distribution, use existing version file
|
||||
try:
|
||||
a = open(filename, "r")
|
||||
lines = a.readlines()
|
||||
git_version = lines[-1].split('"')[1]
|
||||
except Exception:
|
||||
pass
|
||||
finally:
|
||||
a.close()
|
||||
|
||||
text = """# THIS FILE IS GENERATED FROM SPACY SETUP.PY
|
||||
#
|
||||
GIT_VERSION = "%(git_version)s"
|
||||
"""
|
||||
a = open(filename, "w")
|
||||
try:
|
||||
a.write(text % {"git_version": git_version})
|
||||
finally:
|
||||
a.close()
|
||||
|
||||
|
||||
def clean(path):
|
||||
for path in path.glob("**/*"):
|
||||
if path.is_file() and path.suffix in (".so", ".cpp", ".html"):
|
||||
|
|
@ -126,6 +173,7 @@ def clean(path):
|
|||
|
||||
|
||||
def setup_package():
|
||||
write_git_info_py()
|
||||
if len(sys.argv) > 1 and sys.argv[1] == "clean":
|
||||
return clean(PACKAGE_ROOT)
|
||||
|
||||
|
|
|
|||
|
|
@ -31,6 +31,41 @@ class EnglishDefaults(Language.Defaults):
|
|||
{"tags": ["``", "''"], "variants": [('"', '"'), ("“", "”")]},
|
||||
]
|
||||
|
||||
@classmethod
|
||||
def is_base_form(cls, univ_pos, morphology=None):
|
||||
"""
|
||||
Check whether we're dealing with an uninflected paradigm, so we can
|
||||
avoid lemmatization entirely.
|
||||
|
||||
univ_pos (unicode / int): The token's universal part-of-speech tag.
|
||||
morphology (dict): The token's morphological features following the
|
||||
Universal Dependencies scheme.
|
||||
"""
|
||||
if morphology is None:
|
||||
morphology = {}
|
||||
if univ_pos == "noun" and morphology.get("Number") == "sing":
|
||||
return True
|
||||
elif univ_pos == "verb" and morphology.get("VerbForm") == "inf":
|
||||
return True
|
||||
# This maps 'VBP' to base form -- probably just need 'IS_BASE'
|
||||
# morphology
|
||||
elif univ_pos == "verb" and (
|
||||
morphology.get("VerbForm") == "fin"
|
||||
and morphology.get("Tense") == "pres"
|
||||
and morphology.get("Number") is None
|
||||
):
|
||||
return True
|
||||
elif univ_pos == "adj" and morphology.get("Degree") == "pos":
|
||||
return True
|
||||
elif morphology.get("VerbForm") == "inf":
|
||||
return True
|
||||
elif morphology.get("VerbForm") == "none":
|
||||
return True
|
||||
elif morphology.get("Degree") == "pos":
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
class English(Language):
|
||||
lang = "en"
|
||||
|
|
|
|||
|
|
@ -41,9 +41,6 @@ class FrenchLemmatizer(Lemmatizer):
|
|||
univ_pos = "sconj"
|
||||
else:
|
||||
return [self.lookup(string)]
|
||||
# See Issue #435 for example of where this logic is requied.
|
||||
if self.is_base_form(univ_pos, morphology):
|
||||
return list(set([string.lower()]))
|
||||
index_table = self.lookups.get_table("lemma_index", {})
|
||||
exc_table = self.lookups.get_table("lemma_exc", {})
|
||||
rules_table = self.lookups.get_table("lemma_rules", {})
|
||||
|
|
|
|||
|
|
@ -8,6 +8,6 @@ Example sentences to test spaCy and its language models.
|
|||
sentences = [
|
||||
"Լոնդոնը Միացյալ Թագավորության մեծ քաղաք է։",
|
||||
"Ո՞վ է Ֆրանսիայի նախագահը։",
|
||||
"Որն է Միացյալ Նահանգների մայրաքաղաքը։",
|
||||
"Ո՞րն է Միացյալ Նահանգների մայրաքաղաքը։",
|
||||
"Ե՞րբ է ծնվել Բարաք Օբաման։",
|
||||
]
|
||||
|
|
|
|||
|
|
@ -15,14 +15,15 @@ _num_words = [
|
|||
"տասը",
|
||||
"տասնմեկ",
|
||||
"տասներկու",
|
||||
"տասներեք",
|
||||
"տասնչորս",
|
||||
"տասնհինգ",
|
||||
"տասնվեց",
|
||||
"տասնյոթ",
|
||||
"տասնութ",
|
||||
"տասնինը",
|
||||
"քսան" "երեսուն",
|
||||
"տասներեք",
|
||||
"տասնչորս",
|
||||
"տասնհինգ",
|
||||
"տասնվեց",
|
||||
"տասնյոթ",
|
||||
"տասնութ",
|
||||
"տասնինը",
|
||||
"քսան",
|
||||
"երեսուն",
|
||||
"քառասուն",
|
||||
"հիսուն",
|
||||
"վաթսուն",
|
||||
|
|
|
|||
|
|
@ -17,12 +17,9 @@ from ... import util
|
|||
|
||||
|
||||
# Hold the attributes we need with convenient names
|
||||
DetailedToken = namedtuple("DetailedToken", ["surface", "pos", "lemma"])
|
||||
|
||||
# Handling for multiple spaces in a row is somewhat awkward, this simplifies
|
||||
# the flow by creating a dummy with the same interface.
|
||||
DummyNode = namedtuple("DummyNode", ["surface", "pos", "lemma"])
|
||||
DummySpace = DummyNode(" ", " ", " ")
|
||||
DetailedToken = namedtuple(
|
||||
"DetailedToken", ["surface", "tag", "inf", "lemma", "reading", "sub_tokens"]
|
||||
)
|
||||
|
||||
|
||||
def try_sudachi_import(split_mode="A"):
|
||||
|
|
@ -49,7 +46,7 @@ def try_sudachi_import(split_mode="A"):
|
|||
)
|
||||
|
||||
|
||||
def resolve_pos(orth, pos, next_pos):
|
||||
def resolve_pos(orth, tag, next_tag):
|
||||
"""If necessary, add a field to the POS tag for UD mapping.
|
||||
Under Universal Dependencies, sometimes the same Unidic POS tag can
|
||||
be mapped differently depending on the literal token or its context
|
||||
|
|
@ -60,127 +57,80 @@ def resolve_pos(orth, pos, next_pos):
|
|||
# Some tokens have their UD tag decided based on the POS of the following
|
||||
# token.
|
||||
|
||||
# orth based rules
|
||||
if pos[0] in TAG_ORTH_MAP:
|
||||
orth_map = TAG_ORTH_MAP[pos[0]]
|
||||
# apply orth based mapping
|
||||
if tag in TAG_ORTH_MAP:
|
||||
orth_map = TAG_ORTH_MAP[tag]
|
||||
if orth in orth_map:
|
||||
return orth_map[orth], None
|
||||
return orth_map[orth], None # current_pos, next_pos
|
||||
|
||||
# tag bi-gram mapping
|
||||
if next_pos:
|
||||
tag_bigram = pos[0], next_pos[0]
|
||||
# apply tag bi-gram mapping
|
||||
if next_tag:
|
||||
tag_bigram = tag, next_tag
|
||||
if tag_bigram in TAG_BIGRAM_MAP:
|
||||
bipos = TAG_BIGRAM_MAP[tag_bigram]
|
||||
if bipos[0] is None:
|
||||
return TAG_MAP[pos[0]][POS], bipos[1]
|
||||
current_pos, next_pos = TAG_BIGRAM_MAP[tag_bigram]
|
||||
if current_pos is None: # apply tag uni-gram mapping for current_pos
|
||||
return (
|
||||
TAG_MAP[tag][POS],
|
||||
next_pos,
|
||||
) # only next_pos is identified by tag bi-gram mapping
|
||||
else:
|
||||
return bipos
|
||||
return current_pos, next_pos
|
||||
|
||||
return TAG_MAP[pos[0]][POS], None
|
||||
# apply tag uni-gram mapping
|
||||
return TAG_MAP[tag][POS], None
|
||||
|
||||
|
||||
# Use a mapping of paired punctuation to avoid splitting quoted sentences.
|
||||
pairpunct = {"「": "」", "『": "』", "【": "】"}
|
||||
|
||||
|
||||
def separate_sentences(doc):
|
||||
"""Given a doc, mark tokens that start sentences based on Unidic tags.
|
||||
"""
|
||||
|
||||
stack = [] # save paired punctuation
|
||||
|
||||
for i, token in enumerate(doc[:-2]):
|
||||
# Set all tokens after the first to false by default. This is necessary
|
||||
# for the doc code to be aware we've done sentencization, see
|
||||
# `is_sentenced`.
|
||||
token.sent_start = i == 0
|
||||
if token.tag_:
|
||||
if token.tag_ == "補助記号-括弧開":
|
||||
ts = str(token)
|
||||
if ts in pairpunct:
|
||||
stack.append(pairpunct[ts])
|
||||
elif stack and ts == stack[-1]:
|
||||
stack.pop()
|
||||
|
||||
if token.tag_ == "補助記号-句点":
|
||||
next_token = doc[i + 1]
|
||||
if next_token.tag_ != token.tag_ and not stack:
|
||||
next_token.sent_start = True
|
||||
|
||||
|
||||
def get_dtokens(tokenizer, text):
|
||||
tokens = tokenizer.tokenize(text)
|
||||
words = []
|
||||
for ti, token in enumerate(tokens):
|
||||
tag = "-".join([xx for xx in token.part_of_speech()[:4] if xx != "*"])
|
||||
inf = "-".join([xx for xx in token.part_of_speech()[4:] if xx != "*"])
|
||||
dtoken = DetailedToken(token.surface(), (tag, inf), token.dictionary_form())
|
||||
if ti > 0 and words[-1].pos[0] == "空白" and tag == "空白":
|
||||
# don't add multiple space tokens in a row
|
||||
continue
|
||||
words.append(dtoken)
|
||||
|
||||
# remove empty tokens. These can be produced with characters like … that
|
||||
# Sudachi normalizes internally.
|
||||
words = [ww for ww in words if len(ww.surface) > 0]
|
||||
return words
|
||||
|
||||
|
||||
def get_words_lemmas_tags_spaces(dtokens, text, gap_tag=("空白", "")):
|
||||
def get_dtokens_and_spaces(dtokens, text, gap_tag="空白"):
|
||||
# Compare the content of tokens and text, first
|
||||
words = [x.surface for x in dtokens]
|
||||
if "".join("".join(words).split()) != "".join(text.split()):
|
||||
raise ValueError(Errors.E194.format(text=text, words=words))
|
||||
text_words = []
|
||||
text_lemmas = []
|
||||
text_tags = []
|
||||
|
||||
text_dtokens = []
|
||||
text_spaces = []
|
||||
text_pos = 0
|
||||
# handle empty and whitespace-only texts
|
||||
if len(words) == 0:
|
||||
return text_words, text_lemmas, text_tags, text_spaces
|
||||
return text_dtokens, text_spaces
|
||||
elif len([word for word in words if not word.isspace()]) == 0:
|
||||
assert text.isspace()
|
||||
text_words = [text]
|
||||
text_lemmas = [text]
|
||||
text_tags = [gap_tag]
|
||||
text_dtokens = [DetailedToken(text, gap_tag, "", text, None, None)]
|
||||
text_spaces = [False]
|
||||
return text_words, text_lemmas, text_tags, text_spaces
|
||||
# normalize words to remove all whitespace tokens
|
||||
norm_words, norm_dtokens = zip(
|
||||
*[
|
||||
(word, dtokens)
|
||||
for word, dtokens in zip(words, dtokens)
|
||||
if not word.isspace()
|
||||
]
|
||||
)
|
||||
# align words with text
|
||||
for word, dtoken in zip(norm_words, norm_dtokens):
|
||||
return text_dtokens, text_spaces
|
||||
|
||||
# align words and dtokens by referring text, and insert gap tokens for the space char spans
|
||||
for word, dtoken in zip(words, dtokens):
|
||||
# skip all space tokens
|
||||
if word.isspace():
|
||||
continue
|
||||
try:
|
||||
word_start = text[text_pos:].index(word)
|
||||
except ValueError:
|
||||
raise ValueError(Errors.E194.format(text=text, words=words))
|
||||
|
||||
# space token
|
||||
if word_start > 0:
|
||||
w = text[text_pos : text_pos + word_start]
|
||||
text_words.append(w)
|
||||
text_lemmas.append(w)
|
||||
text_tags.append(gap_tag)
|
||||
text_dtokens.append(DetailedToken(w, gap_tag, "", w, None, None))
|
||||
text_spaces.append(False)
|
||||
text_pos += word_start
|
||||
text_words.append(word)
|
||||
text_lemmas.append(dtoken.lemma)
|
||||
text_tags.append(dtoken.pos)
|
||||
|
||||
# content word
|
||||
text_dtokens.append(dtoken)
|
||||
text_spaces.append(False)
|
||||
text_pos += len(word)
|
||||
# poll a space char after the word
|
||||
if text_pos < len(text) and text[text_pos] == " ":
|
||||
text_spaces[-1] = True
|
||||
text_pos += 1
|
||||
|
||||
# trailing space token
|
||||
if text_pos < len(text):
|
||||
w = text[text_pos:]
|
||||
text_words.append(w)
|
||||
text_lemmas.append(w)
|
||||
text_tags.append(gap_tag)
|
||||
text_dtokens.append(DetailedToken(w, gap_tag, "", w, None, None))
|
||||
text_spaces.append(False)
|
||||
return text_words, text_lemmas, text_tags, text_spaces
|
||||
|
||||
return text_dtokens, text_spaces
|
||||
|
||||
|
||||
class JapaneseTokenizer(DummyTokenizer):
|
||||
|
|
@ -190,29 +140,96 @@ class JapaneseTokenizer(DummyTokenizer):
|
|||
self.tokenizer = try_sudachi_import(self.split_mode)
|
||||
|
||||
def __call__(self, text):
|
||||
dtokens = get_dtokens(self.tokenizer, text)
|
||||
# convert sudachipy.morpheme.Morpheme to DetailedToken and merge continuous spaces
|
||||
sudachipy_tokens = self.tokenizer.tokenize(text)
|
||||
dtokens = self._get_dtokens(sudachipy_tokens)
|
||||
dtokens, spaces = get_dtokens_and_spaces(dtokens, text)
|
||||
|
||||
words, lemmas, unidic_tags, spaces = get_words_lemmas_tags_spaces(dtokens, text)
|
||||
# create Doc with tag bi-gram based part-of-speech identification rules
|
||||
words, tags, inflections, lemmas, readings, sub_tokens_list = (
|
||||
zip(*dtokens) if dtokens else [[]] * 6
|
||||
)
|
||||
sub_tokens_list = list(sub_tokens_list)
|
||||
doc = Doc(self.vocab, words=words, spaces=spaces)
|
||||
next_pos = None
|
||||
for idx, (token, lemma, unidic_tag) in enumerate(zip(doc, lemmas, unidic_tags)):
|
||||
token.tag_ = unidic_tag[0]
|
||||
if next_pos:
|
||||
next_pos = None # for bi-gram rules
|
||||
for idx, (token, dtoken) in enumerate(zip(doc, dtokens)):
|
||||
token.tag_ = dtoken.tag
|
||||
if next_pos: # already identified in previous iteration
|
||||
token.pos = next_pos
|
||||
next_pos = None
|
||||
else:
|
||||
token.pos, next_pos = resolve_pos(
|
||||
token.orth_,
|
||||
unidic_tag,
|
||||
unidic_tags[idx + 1] if idx + 1 < len(unidic_tags) else None,
|
||||
dtoken.tag,
|
||||
tags[idx + 1] if idx + 1 < len(tags) else None,
|
||||
)
|
||||
|
||||
# if there's no lemma info (it's an unk) just use the surface
|
||||
token.lemma_ = lemma
|
||||
doc.user_data["unidic_tags"] = unidic_tags
|
||||
token.lemma_ = dtoken.lemma if dtoken.lemma else dtoken.surface
|
||||
|
||||
doc.user_data["inflections"] = inflections
|
||||
doc.user_data["reading_forms"] = readings
|
||||
doc.user_data["sub_tokens"] = sub_tokens_list
|
||||
|
||||
return doc
|
||||
|
||||
def _get_dtokens(self, sudachipy_tokens, need_sub_tokens=True):
|
||||
sub_tokens_list = (
|
||||
self._get_sub_tokens(sudachipy_tokens) if need_sub_tokens else None
|
||||
)
|
||||
dtokens = [
|
||||
DetailedToken(
|
||||
token.surface(), # orth
|
||||
"-".join([xx for xx in token.part_of_speech()[:4] if xx != "*"]), # tag
|
||||
",".join([xx for xx in token.part_of_speech()[4:] if xx != "*"]), # inf
|
||||
token.dictionary_form(), # lemma
|
||||
token.reading_form(), # user_data['reading_forms']
|
||||
sub_tokens_list[idx]
|
||||
if sub_tokens_list
|
||||
else None, # user_data['sub_tokens']
|
||||
)
|
||||
for idx, token in enumerate(sudachipy_tokens)
|
||||
if len(token.surface()) > 0
|
||||
# remove empty tokens which can be produced with characters like … that
|
||||
]
|
||||
# Sudachi normalizes internally and outputs each space char as a token.
|
||||
# This is the preparation for get_dtokens_and_spaces() to merge the continuous space tokens
|
||||
return [
|
||||
t
|
||||
for idx, t in enumerate(dtokens)
|
||||
if idx == 0
|
||||
or not t.surface.isspace()
|
||||
or t.tag != "空白"
|
||||
or not dtokens[idx - 1].surface.isspace()
|
||||
or dtokens[idx - 1].tag != "空白"
|
||||
]
|
||||
|
||||
def _get_sub_tokens(self, sudachipy_tokens):
|
||||
if (
|
||||
self.split_mode is None or self.split_mode == "A"
|
||||
): # do nothing for default split mode
|
||||
return None
|
||||
|
||||
sub_tokens_list = [] # list of (list of list of DetailedToken | None)
|
||||
for token in sudachipy_tokens:
|
||||
sub_a = token.split(self.tokenizer.SplitMode.A)
|
||||
if len(sub_a) == 1: # no sub tokens
|
||||
sub_tokens_list.append(None)
|
||||
elif self.split_mode == "B":
|
||||
sub_tokens_list.append([self._get_dtokens(sub_a, False)])
|
||||
else: # "C"
|
||||
sub_b = token.split(self.tokenizer.SplitMode.B)
|
||||
if len(sub_a) == len(sub_b):
|
||||
dtokens = self._get_dtokens(sub_a, False)
|
||||
sub_tokens_list.append([dtokens, dtokens])
|
||||
else:
|
||||
sub_tokens_list.append(
|
||||
[
|
||||
self._get_dtokens(sub_a, False),
|
||||
self._get_dtokens(sub_b, False),
|
||||
]
|
||||
)
|
||||
return sub_tokens_list
|
||||
|
||||
def _get_config(self):
|
||||
config = OrderedDict((("split_mode", self.split_mode),))
|
||||
return config
|
||||
|
|
|
|||
|
|
@ -1,176 +0,0 @@
|
|||
POS_PHRASE_MAP = {
|
||||
"NOUN": "NP",
|
||||
"NUM": "NP",
|
||||
"PRON": "NP",
|
||||
"PROPN": "NP",
|
||||
"VERB": "VP",
|
||||
"ADJ": "ADJP",
|
||||
"ADV": "ADVP",
|
||||
"CCONJ": "CCONJP",
|
||||
}
|
||||
|
||||
|
||||
# return value: [(bunsetu_tokens, phrase_type={'NP', 'VP', 'ADJP', 'ADVP'}, phrase_tokens)]
|
||||
def yield_bunsetu(doc, debug=False):
|
||||
bunsetu = []
|
||||
bunsetu_may_end = False
|
||||
phrase_type = None
|
||||
phrase = None
|
||||
prev = None
|
||||
prev_tag = None
|
||||
prev_dep = None
|
||||
prev_head = None
|
||||
for t in doc:
|
||||
pos = t.pos_
|
||||
pos_type = POS_PHRASE_MAP.get(pos, None)
|
||||
tag = t.tag_
|
||||
dep = t.dep_
|
||||
head = t.head.i
|
||||
if debug:
|
||||
print(
|
||||
t.i,
|
||||
t.orth_,
|
||||
pos,
|
||||
pos_type,
|
||||
dep,
|
||||
head,
|
||||
bunsetu_may_end,
|
||||
phrase_type,
|
||||
phrase,
|
||||
bunsetu,
|
||||
)
|
||||
|
||||
# DET is always an individual bunsetu
|
||||
if pos == "DET":
|
||||
if bunsetu:
|
||||
yield bunsetu, phrase_type, phrase
|
||||
yield [t], None, None
|
||||
bunsetu = []
|
||||
bunsetu_may_end = False
|
||||
phrase_type = None
|
||||
phrase = None
|
||||
|
||||
# PRON or Open PUNCT always splits bunsetu
|
||||
elif tag == "補助記号-括弧開":
|
||||
if bunsetu:
|
||||
yield bunsetu, phrase_type, phrase
|
||||
bunsetu = [t]
|
||||
bunsetu_may_end = True
|
||||
phrase_type = None
|
||||
phrase = None
|
||||
|
||||
# bunsetu head not appeared
|
||||
elif phrase_type is None:
|
||||
if bunsetu and prev_tag == "補助記号-読点":
|
||||
yield bunsetu, phrase_type, phrase
|
||||
bunsetu = []
|
||||
bunsetu_may_end = False
|
||||
phrase_type = None
|
||||
phrase = None
|
||||
bunsetu.append(t)
|
||||
if pos_type: # begin phrase
|
||||
phrase = [t]
|
||||
phrase_type = pos_type
|
||||
if pos_type in {"ADVP", "CCONJP"}:
|
||||
bunsetu_may_end = True
|
||||
|
||||
# entering new bunsetu
|
||||
elif pos_type and (
|
||||
pos_type != phrase_type
|
||||
or bunsetu_may_end # different phrase type arises # same phrase type but bunsetu already ended
|
||||
):
|
||||
# exceptional case: NOUN to VERB
|
||||
if (
|
||||
phrase_type == "NP"
|
||||
and pos_type == "VP"
|
||||
and prev_dep == "compound"
|
||||
and prev_head == t.i
|
||||
):
|
||||
bunsetu.append(t)
|
||||
phrase_type = "VP"
|
||||
phrase.append(t)
|
||||
# exceptional case: VERB to NOUN
|
||||
elif (
|
||||
phrase_type == "VP"
|
||||
and pos_type == "NP"
|
||||
and (
|
||||
prev_dep == "compound"
|
||||
and prev_head == t.i
|
||||
or dep == "compound"
|
||||
and prev == head
|
||||
or prev_dep == "nmod"
|
||||
and prev_head == t.i
|
||||
)
|
||||
):
|
||||
bunsetu.append(t)
|
||||
phrase_type = "NP"
|
||||
phrase.append(t)
|
||||
else:
|
||||
yield bunsetu, phrase_type, phrase
|
||||
bunsetu = [t]
|
||||
bunsetu_may_end = False
|
||||
phrase_type = pos_type
|
||||
phrase = [t]
|
||||
|
||||
# NOUN bunsetu
|
||||
elif phrase_type == "NP":
|
||||
bunsetu.append(t)
|
||||
if not bunsetu_may_end and (
|
||||
(
|
||||
(pos_type == "NP" or pos == "SYM")
|
||||
and (prev_head == t.i or prev_head == head)
|
||||
and prev_dep in {"compound", "nummod"}
|
||||
)
|
||||
or (
|
||||
pos == "PART"
|
||||
and (prev == head or prev_head == head)
|
||||
and dep == "mark"
|
||||
)
|
||||
):
|
||||
phrase.append(t)
|
||||
else:
|
||||
bunsetu_may_end = True
|
||||
|
||||
# VERB bunsetu
|
||||
elif phrase_type == "VP":
|
||||
bunsetu.append(t)
|
||||
if (
|
||||
not bunsetu_may_end
|
||||
and pos == "VERB"
|
||||
and prev_head == t.i
|
||||
and prev_dep == "compound"
|
||||
):
|
||||
phrase.append(t)
|
||||
else:
|
||||
bunsetu_may_end = True
|
||||
|
||||
# ADJ bunsetu
|
||||
elif phrase_type == "ADJP" and tag != "連体詞":
|
||||
bunsetu.append(t)
|
||||
if not bunsetu_may_end and (
|
||||
(
|
||||
pos == "NOUN"
|
||||
and (prev_head == t.i or prev_head == head)
|
||||
and prev_dep in {"amod", "compound"}
|
||||
)
|
||||
or (
|
||||
pos == "PART"
|
||||
and (prev == head or prev_head == head)
|
||||
and dep == "mark"
|
||||
)
|
||||
):
|
||||
phrase.append(t)
|
||||
else:
|
||||
bunsetu_may_end = True
|
||||
|
||||
# other bunsetu
|
||||
else:
|
||||
bunsetu.append(t)
|
||||
|
||||
prev = t.i
|
||||
prev_tag = t.tag_
|
||||
prev_dep = t.dep_
|
||||
prev_head = head
|
||||
|
||||
if bunsetu:
|
||||
yield bunsetu, phrase_type, phrase
|
||||
|
|
@ -39,7 +39,11 @@ def check_spaces(text, tokens):
|
|||
class KoreanTokenizer(DummyTokenizer):
|
||||
def __init__(self, cls, nlp=None):
|
||||
self.vocab = nlp.vocab if nlp is not None else cls.create_vocab(nlp)
|
||||
self.Tokenizer = try_mecab_import()
|
||||
MeCab = try_mecab_import()
|
||||
self.mecab_tokenizer = MeCab("-F%f[0],%f[7]")
|
||||
|
||||
def __del__(self):
|
||||
self.mecab_tokenizer.__del__()
|
||||
|
||||
def __call__(self, text):
|
||||
dtokens = list(self.detailed_tokens(text))
|
||||
|
|
@ -55,17 +59,16 @@ class KoreanTokenizer(DummyTokenizer):
|
|||
def detailed_tokens(self, text):
|
||||
# 품사 태그(POS)[0], 의미 부류(semantic class)[1], 종성 유무(jongseong)[2], 읽기(reading)[3],
|
||||
# 타입(type)[4], 첫번째 품사(start pos)[5], 마지막 품사(end pos)[6], 표현(expression)[7], *
|
||||
with self.Tokenizer("-F%f[0],%f[7]") as tokenizer:
|
||||
for node in tokenizer.parse(text, as_nodes=True):
|
||||
if node.is_eos():
|
||||
break
|
||||
surface = node.surface
|
||||
feature = node.feature
|
||||
tag, _, expr = feature.partition(",")
|
||||
lemma, _, remainder = expr.partition("/")
|
||||
if lemma == "*":
|
||||
lemma = surface
|
||||
yield {"surface": surface, "lemma": lemma, "tag": tag}
|
||||
for node in self.mecab_tokenizer.parse(text, as_nodes=True):
|
||||
if node.is_eos():
|
||||
break
|
||||
surface = node.surface
|
||||
feature = node.feature
|
||||
tag, _, expr = feature.partition(",")
|
||||
lemma, _, remainder = expr.partition("/")
|
||||
if lemma == "*":
|
||||
lemma = surface
|
||||
yield {"surface": surface, "lemma": lemma, "tag": tag}
|
||||
|
||||
|
||||
class KoreanDefaults(Language.Defaults):
|
||||
|
|
|
|||
23
spacy/lang/ne/__init__.py
Normal file
23
spacy/lang/ne/__init__.py
Normal file
|
|
@ -0,0 +1,23 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
|
||||
from .stop_words import STOP_WORDS
|
||||
from .lex_attrs import LEX_ATTRS
|
||||
|
||||
from ...language import Language
|
||||
from ...attrs import LANG
|
||||
|
||||
|
||||
class NepaliDefaults(Language.Defaults):
|
||||
lex_attr_getters = dict(Language.Defaults.lex_attr_getters)
|
||||
lex_attr_getters.update(LEX_ATTRS)
|
||||
lex_attr_getters[LANG] = lambda text: "ne" # Nepali language ISO code
|
||||
stop_words = STOP_WORDS
|
||||
|
||||
|
||||
class Nepali(Language):
|
||||
lang = "ne"
|
||||
Defaults = NepaliDefaults
|
||||
|
||||
|
||||
__all__ = ["Nepali"]
|
||||
22
spacy/lang/ne/examples.py
Normal file
22
spacy/lang/ne/examples.py
Normal file
|
|
@ -0,0 +1,22 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
|
||||
|
||||
"""
|
||||
Example sentences to test spaCy and its language models.
|
||||
|
||||
>>> from spacy.lang.ne.examples import sentences
|
||||
>>> docs = nlp.pipe(sentences)
|
||||
"""
|
||||
|
||||
|
||||
sentences = [
|
||||
"एप्पलले अमेरिकी स्टार्टअप १ अर्ब डलरमा किन्ने सोच्दै छ",
|
||||
"स्वायत्त कारहरूले बीमा दायित्व निर्माताहरु तिर बदल्छन्",
|
||||
"स्यान फ्रांसिस्कोले फुटपाथ वितरण रोबोटहरु प्रतिबंध गर्ने विचार गर्दै छ",
|
||||
"लन्डन यूनाइटेड किंगडमको एक ठूलो शहर हो।",
|
||||
"तिमी कहाँ छौ?",
|
||||
"फ्रान्स को राष्ट्रपति को हो?",
|
||||
"संयुक्त राज्यको राजधानी के हो?",
|
||||
"बराक ओबामा कहिले कहिले जन्मेका हुन्?",
|
||||
]
|
||||
98
spacy/lang/ne/lex_attrs.py
Normal file
98
spacy/lang/ne/lex_attrs.py
Normal file
|
|
@ -0,0 +1,98 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
|
||||
from ..norm_exceptions import BASE_NORMS
|
||||
from ...attrs import NORM, LIKE_NUM
|
||||
|
||||
|
||||
# fmt: off
|
||||
_stem_suffixes = [
|
||||
["ा", "ि", "ी", "ु", "ू", "ृ", "े", "ै", "ो", "ौ"],
|
||||
["ँ", "ं", "्", "ः"],
|
||||
["लाई", "ले", "बाट", "को", "मा", "हरू"],
|
||||
["हरूलाई", "हरूले", "हरूबाट", "हरूको", "हरूमा"],
|
||||
["इलो", "िलो", "नु", "ाउनु", "ई", "इन", "इन्", "इनन्"],
|
||||
["एँ", "इँन्", "इस्", "इनस्", "यो", "एन", "यौं", "एनौं", "ए", "एनन्"],
|
||||
["छु", "छौँ", "छस्", "छौ", "छ", "छन्", "छेस्", "छे", "छ्यौ", "छिन्", "हुन्छ"],
|
||||
["दै", "दिन", "दिँन", "दैनस्", "दैन", "दैनौँ", "दैनौं", "दैनन्"],
|
||||
["हुन्न", "न्न", "न्न्स्", "न्नौं", "न्नौ", "न्न्न्", "िई"],
|
||||
["अ", "ओ", "ऊ", "अरी", "साथ", "वित्तिकै", "पूर्वक"],
|
||||
["याइ", "ाइ", "बार", "वार", "चाँहि"],
|
||||
["ने", "ेको", "ेकी", "ेका", "ेर", "दै", "तै", "िकन", "उ", "न", "नन्"]
|
||||
]
|
||||
# fmt: on
|
||||
|
||||
# reference 1: https://en.wikipedia.org/wiki/Numbers_in_Nepali_language
|
||||
# reference 2: https://www.imnepal.com/nepali-numbers/
|
||||
_num_words = [
|
||||
"शुन्य",
|
||||
"एक",
|
||||
"दुई",
|
||||
"तीन",
|
||||
"चार",
|
||||
"पाँच",
|
||||
"छ",
|
||||
"सात",
|
||||
"आठ",
|
||||
"नौ",
|
||||
"दश",
|
||||
"एघार",
|
||||
"बाह्र",
|
||||
"तेह्र",
|
||||
"चौध",
|
||||
"पन्ध्र",
|
||||
"सोह्र",
|
||||
"सोह्र",
|
||||
"सत्र",
|
||||
"अठार",
|
||||
"उन्नाइस",
|
||||
"बीस",
|
||||
"तीस",
|
||||
"चालीस",
|
||||
"पचास",
|
||||
"साठी",
|
||||
"सत्तरी",
|
||||
"असी",
|
||||
"नब्बे",
|
||||
"सय",
|
||||
"हजार",
|
||||
"लाख",
|
||||
"करोड",
|
||||
"अर्ब",
|
||||
"खर्ब",
|
||||
]
|
||||
|
||||
|
||||
def norm(string):
|
||||
# normalise base exceptions, e.g. punctuation or currency symbols
|
||||
if string in BASE_NORMS:
|
||||
return BASE_NORMS[string]
|
||||
# set stem word as norm, if available, adapted from:
|
||||
# https://github.com/explosion/spaCy/blob/master/spacy/lang/hi/lex_attrs.py
|
||||
# https://www.researchgate.net/publication/237261579_Structure_of_Nepali_Grammar
|
||||
for suffix_group in reversed(_stem_suffixes):
|
||||
length = len(suffix_group[0])
|
||||
if len(string) <= length:
|
||||
break
|
||||
for suffix in suffix_group:
|
||||
if string.endswith(suffix):
|
||||
return string[:-length]
|
||||
return string
|
||||
|
||||
|
||||
def like_num(text):
|
||||
if text.startswith(("+", "-", "±", "~")):
|
||||
text = text[1:]
|
||||
text = text.replace(", ", "").replace(".", "")
|
||||
if text.isdigit():
|
||||
return True
|
||||
if text.count("/") == 1:
|
||||
num, denom = text.split("/")
|
||||
if num.isdigit() and denom.isdigit():
|
||||
return True
|
||||
if text.lower() in _num_words:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
LEX_ATTRS = {NORM: norm, LIKE_NUM: like_num}
|
||||
498
spacy/lang/ne/stop_words.py
Normal file
498
spacy/lang/ne/stop_words.py
Normal file
|
|
@ -0,0 +1,498 @@
|
|||
# coding: utf8
|
||||
from __future__ import unicode_literals
|
||||
|
||||
|
||||
# Source: https://github.com/sanjaalcorps/NepaliStopWords/blob/master/NepaliStopWords.txt
|
||||
|
||||
STOP_WORDS = set(
|
||||
"""
|
||||
अक्सर
|
||||
अगाडि
|
||||
अगाडी
|
||||
अघि
|
||||
अझै
|
||||
अठार
|
||||
अथवा
|
||||
अनि
|
||||
अनुसार
|
||||
अन्तर्गत
|
||||
अन्य
|
||||
अन्यत्र
|
||||
अन्यथा
|
||||
अब
|
||||
अरु
|
||||
अरुलाई
|
||||
अरू
|
||||
अर्को
|
||||
अर्थात
|
||||
अर्थात्
|
||||
अलग
|
||||
अलि
|
||||
अवस्था
|
||||
अहिले
|
||||
आए
|
||||
आएका
|
||||
आएको
|
||||
आज
|
||||
आजको
|
||||
आठ
|
||||
आत्म
|
||||
आदि
|
||||
आदिलाई
|
||||
आफनो
|
||||
आफू
|
||||
आफूलाई
|
||||
आफै
|
||||
आफैँ
|
||||
आफ्नै
|
||||
आफ्नो
|
||||
आयो
|
||||
उ
|
||||
उक्त
|
||||
उदाहरण
|
||||
उनको
|
||||
उनलाई
|
||||
उनले
|
||||
उनि
|
||||
उनी
|
||||
उनीहरुको
|
||||
उन्नाइस
|
||||
उप
|
||||
उसको
|
||||
उसलाई
|
||||
उसले
|
||||
उहालाई
|
||||
ऊ
|
||||
एउटा
|
||||
एउटै
|
||||
एक
|
||||
एकदम
|
||||
एघार
|
||||
ओठ
|
||||
औ
|
||||
औं
|
||||
कता
|
||||
कति
|
||||
कतै
|
||||
कम
|
||||
कमसेकम
|
||||
कसरि
|
||||
कसरी
|
||||
कसै
|
||||
कसैको
|
||||
कसैलाई
|
||||
कसैले
|
||||
कसैसँग
|
||||
कस्तो
|
||||
कहाँबाट
|
||||
कहिलेकाहीं
|
||||
का
|
||||
काम
|
||||
कारण
|
||||
कि
|
||||
किन
|
||||
किनभने
|
||||
कुन
|
||||
कुनै
|
||||
कुन्नी
|
||||
कुरा
|
||||
कृपया
|
||||
के
|
||||
केहि
|
||||
केही
|
||||
को
|
||||
कोहि
|
||||
कोहिपनि
|
||||
कोही
|
||||
कोहीपनि
|
||||
क्रमशः
|
||||
गए
|
||||
गएको
|
||||
गएर
|
||||
गयौ
|
||||
गरि
|
||||
गरी
|
||||
गरे
|
||||
गरेका
|
||||
गरेको
|
||||
गरेर
|
||||
गरौं
|
||||
गर्छ
|
||||
गर्छन्
|
||||
गर्छु
|
||||
गर्दा
|
||||
गर्दै
|
||||
गर्न
|
||||
गर्नु
|
||||
गर्नुपर्छ
|
||||
गर्ने
|
||||
गैर
|
||||
घर
|
||||
चार
|
||||
चाले
|
||||
चाहनुहुन्छ
|
||||
चाहन्छु
|
||||
चाहिं
|
||||
चाहिए
|
||||
चाहिंले
|
||||
चाहीं
|
||||
चाहेको
|
||||
चाहेर
|
||||
चोटी
|
||||
चौथो
|
||||
चौध
|
||||
छ
|
||||
छन
|
||||
छन्
|
||||
छु
|
||||
छू
|
||||
छैन
|
||||
छैनन्
|
||||
छौ
|
||||
छौं
|
||||
जता
|
||||
जताततै
|
||||
जना
|
||||
जनाको
|
||||
जनालाई
|
||||
जनाले
|
||||
जब
|
||||
जबकि
|
||||
जबकी
|
||||
जसको
|
||||
जसबाट
|
||||
जसमा
|
||||
जसरी
|
||||
जसलाई
|
||||
जसले
|
||||
जस्ता
|
||||
जस्तै
|
||||
जस्तो
|
||||
जस्तोसुकै
|
||||
जहाँ
|
||||
जान
|
||||
जाने
|
||||
जाहिर
|
||||
जुन
|
||||
जुनै
|
||||
जे
|
||||
जो
|
||||
जोपनि
|
||||
जोपनी
|
||||
झैं
|
||||
ठाउँमा
|
||||
ठीक
|
||||
ठूलो
|
||||
त
|
||||
तता
|
||||
तत्काल
|
||||
तथा
|
||||
तथापि
|
||||
तथापी
|
||||
तदनुसार
|
||||
तपाइ
|
||||
तपाई
|
||||
तपाईको
|
||||
तब
|
||||
तर
|
||||
तर्फ
|
||||
तल
|
||||
तसरी
|
||||
तापनि
|
||||
तापनी
|
||||
तिन
|
||||
तिनि
|
||||
तिनिहरुलाई
|
||||
तिनी
|
||||
तिनीहरु
|
||||
तिनीहरुको
|
||||
तिनीहरू
|
||||
तिनीहरूको
|
||||
तिनै
|
||||
तिमी
|
||||
तिर
|
||||
तिरको
|
||||
ती
|
||||
तीन
|
||||
तुरन्त
|
||||
तुरुन्त
|
||||
तुरुन्तै
|
||||
तेश्रो
|
||||
तेस्कारण
|
||||
तेस्रो
|
||||
तेह्र
|
||||
तैपनि
|
||||
तैपनी
|
||||
त्यत्तिकै
|
||||
त्यत्तिकैमा
|
||||
त्यस
|
||||
त्यसकारण
|
||||
त्यसको
|
||||
त्यसले
|
||||
त्यसैले
|
||||
त्यसो
|
||||
त्यस्तै
|
||||
त्यस्तो
|
||||
त्यहाँ
|
||||
त्यहिँ
|
||||
त्यही
|
||||
त्यहीँ
|
||||
त्यहीं
|
||||
त्यो
|
||||
त्सपछि
|
||||
त्सैले
|
||||
थप
|
||||
थरि
|
||||
थरी
|
||||
थाहा
|
||||
थिए
|
||||
थिएँ
|
||||
थिएन
|
||||
थियो
|
||||
दर्ता
|
||||
दश
|
||||
दिए
|
||||
दिएको
|
||||
दिन
|
||||
दिनुभएको
|
||||
दिनुहुन्छ
|
||||
दुइ
|
||||
दुइवटा
|
||||
दुई
|
||||
देखि
|
||||
देखिन्छ
|
||||
देखियो
|
||||
देखे
|
||||
देखेको
|
||||
देखेर
|
||||
दोश्री
|
||||
दोश्रो
|
||||
दोस्रो
|
||||
द्वारा
|
||||
धन्न
|
||||
धेरै
|
||||
धौ
|
||||
न
|
||||
नगर्नु
|
||||
नगर्नू
|
||||
नजिकै
|
||||
नत्र
|
||||
नत्रभने
|
||||
नभई
|
||||
नभएको
|
||||
नभनेर
|
||||
नयाँ
|
||||
नि
|
||||
निकै
|
||||
निम्ति
|
||||
निम्न
|
||||
निम्नानुसार
|
||||
निर्दिष्ट
|
||||
नै
|
||||
नौ
|
||||
पक्का
|
||||
पक्कै
|
||||
पछाडि
|
||||
पछाडी
|
||||
पछि
|
||||
पछिल्लो
|
||||
पछी
|
||||
पटक
|
||||
पनि
|
||||
पन्ध्र
|
||||
पर्छ
|
||||
पर्थ्यो
|
||||
पर्दैन
|
||||
पर्ने
|
||||
पर्नेमा
|
||||
पर्याप्त
|
||||
पहिले
|
||||
पहिलो
|
||||
पहिल्यै
|
||||
पाँच
|
||||
पांच
|
||||
पाचौँ
|
||||
पाँचौं
|
||||
पिच्छे
|
||||
पूर्व
|
||||
पो
|
||||
प्रति
|
||||
प्रतेक
|
||||
प्रत्यक
|
||||
प्राय
|
||||
प्लस
|
||||
फरक
|
||||
फेरि
|
||||
फेरी
|
||||
बढी
|
||||
बताए
|
||||
बने
|
||||
बरु
|
||||
बाट
|
||||
बारे
|
||||
बाहिर
|
||||
बाहेक
|
||||
बाह्र
|
||||
बिच
|
||||
बिचमा
|
||||
बिरुद्ध
|
||||
बिशेष
|
||||
बिस
|
||||
बीच
|
||||
बीचमा
|
||||
बीस
|
||||
भए
|
||||
भएँ
|
||||
भएका
|
||||
भएकालाई
|
||||
भएको
|
||||
भएन
|
||||
भएर
|
||||
भन
|
||||
भने
|
||||
भनेको
|
||||
भनेर
|
||||
भन्
|
||||
भन्छन्
|
||||
भन्छु
|
||||
भन्दा
|
||||
भन्दै
|
||||
भन्नुभयो
|
||||
भन्ने
|
||||
भन्या
|
||||
भयेन
|
||||
भयो
|
||||
भर
|
||||
भरि
|
||||
भरी
|
||||
भा
|
||||
भित्र
|
||||
भित्री
|
||||
भीत्र
|
||||
म
|
||||
मध्य
|
||||
मध्ये
|
||||
मलाई
|
||||
मा
|
||||
मात्र
|
||||
मात्रै
|
||||
माथि
|
||||
माथी
|
||||
मुख्य
|
||||
मुनि
|
||||
मुन्तिर
|
||||
मेरो
|
||||
मैले
|
||||
यति
|
||||
यथोचित
|
||||
यदि
|
||||
यद्ध्यपि
|
||||
यद्यपि
|
||||
यस
|
||||
यसका
|
||||
यसको
|
||||
यसपछि
|
||||
यसबाहेक
|
||||
यसमा
|
||||
यसरी
|
||||
यसले
|
||||
यसो
|
||||
यस्तै
|
||||
यस्तो
|
||||
यहाँ
|
||||
यहाँसम्म
|
||||
यही
|
||||
या
|
||||
यी
|
||||
यो
|
||||
र
|
||||
रही
|
||||
रहेका
|
||||
रहेको
|
||||
रहेछ
|
||||
राखे
|
||||
राख्छ
|
||||
राम्रो
|
||||
रुपमा
|
||||
रूप
|
||||
रे
|
||||
लगभग
|
||||
लगायत
|
||||
लाई
|
||||
लाख
|
||||
लागि
|
||||
लागेको
|
||||
ले
|
||||
वटा
|
||||
वरीपरी
|
||||
वा
|
||||
वाट
|
||||
वापत
|
||||
वास्तवमा
|
||||
शायद
|
||||
सक्छ
|
||||
सक्ने
|
||||
सँग
|
||||
संग
|
||||
सँगको
|
||||
सँगसँगै
|
||||
सँगै
|
||||
संगै
|
||||
सङ्ग
|
||||
सङ्गको
|
||||
सट्टा
|
||||
सत्र
|
||||
सधै
|
||||
सबै
|
||||
सबैको
|
||||
सबैलाई
|
||||
समय
|
||||
समेत
|
||||
सम्भव
|
||||
सम्म
|
||||
सय
|
||||
सरह
|
||||
सहित
|
||||
सहितै
|
||||
सही
|
||||
साँच्चै
|
||||
सात
|
||||
साथ
|
||||
साथै
|
||||
सायद
|
||||
सारा
|
||||
सुनेको
|
||||
सुनेर
|
||||
सुरु
|
||||
सुरुको
|
||||
सुरुमै
|
||||
सो
|
||||
सोचेको
|
||||
सोचेर
|
||||
सोही
|
||||
सोह्र
|
||||
स्थित
|
||||
स्पष्ट
|
||||
हजार
|
||||
हरे
|
||||
हरेक
|
||||
हामी
|
||||
हामीले
|
||||
हाम्रा
|
||||
हाम्रो
|
||||
हुँदैन
|
||||
हुन
|
||||
हुनत
|
||||
हुनु
|
||||
हुने
|
||||
हुनेछ
|
||||
हुन्
|
||||
हुन्छ
|
||||
हुन्थ्यो
|
||||
हैन
|
||||
हो
|
||||
होइन
|
||||
होकि
|
||||
होला
|
||||
""".split()
|
||||
)
|
||||
|
|
@ -14,7 +14,7 @@ from .stop_words import STOP_WORDS
|
|||
from ... import util
|
||||
|
||||
|
||||
_PKUSEG_INSTALL_MSG = "install it with `pip install pkuseg==0.0.22` or from https://github.com/lancopku/pkuseg-python"
|
||||
_PKUSEG_INSTALL_MSG = "install it with `pip install pkuseg==0.0.25` or from https://github.com/lancopku/pkuseg-python"
|
||||
|
||||
|
||||
def try_jieba_import(segmenter):
|
||||
|
|
|
|||
|
|
@ -32,6 +32,7 @@ from .lang.tag_map import TAG_MAP
|
|||
from .tokens import Doc
|
||||
from .lang.lex_attrs import LEX_ATTRS, is_stop
|
||||
from .errors import Errors, Warnings
|
||||
from .git_info import GIT_VERSION
|
||||
from . import util
|
||||
from . import about
|
||||
|
||||
|
|
@ -44,7 +45,7 @@ class BaseDefaults:
|
|||
def create_lemmatizer(cls, nlp=None, lookups=None):
|
||||
if lookups is None:
|
||||
lookups = cls.create_lookups(nlp=nlp)
|
||||
return Lemmatizer(lookups=lookups)
|
||||
return Lemmatizer(lookups=lookups, is_base_form=cls.is_base_form)
|
||||
|
||||
@classmethod
|
||||
def create_lookups(cls, nlp=None):
|
||||
|
|
@ -116,6 +117,7 @@ class BaseDefaults:
|
|||
tokenizer_exceptions = {}
|
||||
stop_words = set()
|
||||
morph_rules = {}
|
||||
is_base_form = None
|
||||
lex_attr_getters = LEX_ATTRS
|
||||
syntax_iterators = {}
|
||||
resources = {}
|
||||
|
|
@ -212,6 +214,7 @@ class Language:
|
|||
self._meta.setdefault("email", "")
|
||||
self._meta.setdefault("url", "")
|
||||
self._meta.setdefault("license", "")
|
||||
self._meta.setdefault("spacy_git_version", GIT_VERSION)
|
||||
self._meta["vectors"] = {
|
||||
"width": self.vocab.vectors_length,
|
||||
"vectors": len(self.vocab.vectors),
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ class Lemmatizer:
|
|||
def load(cls, *args, **kwargs):
|
||||
raise NotImplementedError(Errors.E172)
|
||||
|
||||
def __init__(self, lookups):
|
||||
def __init__(self, lookups, is_base_form=None):
|
||||
"""Initialize a Lemmatizer.
|
||||
|
||||
lookups (Lookups): The lookups object containing the (optional) tables
|
||||
|
|
@ -22,6 +22,7 @@ class Lemmatizer:
|
|||
RETURNS (Lemmatizer): The newly constructed object.
|
||||
"""
|
||||
self.lookups = lookups
|
||||
self.is_base_form = is_base_form
|
||||
|
||||
def __call__(self, string, univ_pos, morphology=None):
|
||||
"""Lemmatize a string.
|
||||
|
|
@ -42,7 +43,7 @@ class Lemmatizer:
|
|||
if univ_pos in ("", "eol", "space"):
|
||||
return [string.lower()]
|
||||
# See Issue #435 for example of where this logic is requied.
|
||||
if self.is_base_form(univ_pos, morphology):
|
||||
if callable(self.is_base_form) and self.is_base_form(univ_pos, morphology):
|
||||
return [string.lower()]
|
||||
index_table = self.lookups.get_table("lemma_index", {})
|
||||
exc_table = self.lookups.get_table("lemma_exc", {})
|
||||
|
|
|
|||
|
|
@ -346,7 +346,7 @@ cdef class Lexeme:
|
|||
@property
|
||||
def is_oov(self):
|
||||
"""RETURNS (bool): Whether the lexeme is out-of-vocabulary."""
|
||||
return self.orth in self.vocab.vectors
|
||||
return self.orth not in self.vocab.vectors
|
||||
|
||||
property is_stop:
|
||||
"""RETURNS (bool): Whether the lexeme is a stop word."""
|
||||
|
|
|
|||
|
|
@ -117,8 +117,7 @@ class Lookups:
|
|||
"""
|
||||
self._tables = {}
|
||||
for key, value in srsly.msgpack_loads(bytes_data).items():
|
||||
self._tables[key] = Table(key)
|
||||
self._tables[key].update(value)
|
||||
self._tables[key] = Table(key, value)
|
||||
return self
|
||||
|
||||
def to_disk(self, path, filename="lookups.bin", **kwargs):
|
||||
|
|
@ -189,7 +188,7 @@ class Table(OrderedDict):
|
|||
self.name = name
|
||||
# Assume a default size of 1M items
|
||||
self.default_size = 1e6
|
||||
size = len(data) if data and len(data) > 0 else self.default_size
|
||||
size = max(len(data), 1) if data is not None else self.default_size
|
||||
self.bloom = BloomFilter.from_error_rate(size)
|
||||
if data:
|
||||
self.update(data)
|
||||
|
|
|
|||
|
|
@ -781,6 +781,20 @@ class ClozeMultitask(Pipe):
|
|||
if losses is not None:
|
||||
losses[self.name] += loss
|
||||
|
||||
@staticmethod
|
||||
def decode_utf8_predictions(char_array):
|
||||
# The format alternates filling from start and end, and 255 is missing
|
||||
words = []
|
||||
char_array = char_array.reshape((char_array.shape[0], -1, 256))
|
||||
nr_char = char_array.shape[1]
|
||||
char_array = char_array.argmax(axis=-1)
|
||||
for row in char_array:
|
||||
starts = [chr(c) for c in row[::2] if c != 255]
|
||||
ends = [chr(c) for c in row[1::2] if c != 255]
|
||||
word = "".join(starts + list(reversed(ends)))
|
||||
words.append(word)
|
||||
return words
|
||||
|
||||
|
||||
@component("textcat", assigns=["doc.cats"], default_model=default_textcat)
|
||||
class TextCategorizer(Pipe):
|
||||
|
|
@ -949,6 +963,7 @@ cdef class DependencyParser(Parser):
|
|||
assigns = ["token.dep", "token.is_sent_start", "doc.sents"]
|
||||
requires = []
|
||||
TransitionSystem = ArcEager
|
||||
nr_feature = 8
|
||||
|
||||
@property
|
||||
def postprocesses(self):
|
||||
|
|
|
|||
|
|
@ -167,6 +167,11 @@ def nb_tokenizer():
|
|||
return get_lang_class("nb").Defaults.create_tokenizer()
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def ne_tokenizer():
|
||||
return get_lang_class("ne").Defaults.create_tokenizer()
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def nl_tokenizer():
|
||||
return get_lang_class("nl").Defaults.create_tokenizer()
|
||||
|
|
|
|||
|
|
@ -102,10 +102,16 @@ def test_doc_api_getitem(en_tokenizer):
|
|||
)
|
||||
def test_doc_api_serialize(en_tokenizer, text):
|
||||
tokens = en_tokenizer(text)
|
||||
tokens[0].lemma_ = "lemma"
|
||||
tokens[0].norm_ = "norm"
|
||||
tokens[0].ent_kb_id_ = "ent_kb_id"
|
||||
new_tokens = Doc(tokens.vocab).from_bytes(tokens.to_bytes())
|
||||
assert tokens.text == new_tokens.text
|
||||
assert [t.text for t in tokens] == [t.text for t in new_tokens]
|
||||
assert [t.orth for t in tokens] == [t.orth for t in new_tokens]
|
||||
assert new_tokens[0].lemma_ == "lemma"
|
||||
assert new_tokens[0].norm_ == "norm"
|
||||
assert new_tokens[0].ent_kb_id_ == "ent_kb_id"
|
||||
|
||||
new_tokens = Doc(tokens.vocab).from_bytes(
|
||||
tokens.to_bytes(exclude=["tensor"]), exclude=["tensor"]
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
import pytest
|
||||
|
||||
from ...tokenizer.test_naughty_strings import NAUGHTY_STRINGS
|
||||
from spacy.lang.ja import Japanese
|
||||
from spacy.lang.ja import Japanese, DetailedToken
|
||||
|
||||
# fmt: off
|
||||
TOKENIZER_TESTS = [
|
||||
|
|
@ -93,6 +93,57 @@ def test_ja_tokenizer_split_modes(ja_tokenizer, text, len_a, len_b, len_c):
|
|||
assert len(nlp_c(text)) == len_c
|
||||
|
||||
|
||||
@pytest.mark.parametrize("text,sub_tokens_list_a,sub_tokens_list_b,sub_tokens_list_c",
|
||||
[
|
||||
(
|
||||
"選挙管理委員会",
|
||||
[None, None, None, None],
|
||||
[None, None, [
|
||||
[
|
||||
DetailedToken(surface='委員', tag='名詞-普通名詞-一般', inf='', lemma='委員', reading='イイン', sub_tokens=None),
|
||||
DetailedToken(surface='会', tag='名詞-普通名詞-一般', inf='', lemma='会', reading='カイ', sub_tokens=None),
|
||||
]
|
||||
]],
|
||||
[[
|
||||
[
|
||||
DetailedToken(surface='選挙', tag='名詞-普通名詞-サ変可能', inf='', lemma='選挙', reading='センキョ', sub_tokens=None),
|
||||
DetailedToken(surface='管理', tag='名詞-普通名詞-サ変可能', inf='', lemma='管理', reading='カンリ', sub_tokens=None),
|
||||
DetailedToken(surface='委員', tag='名詞-普通名詞-一般', inf='', lemma='委員', reading='イイン', sub_tokens=None),
|
||||
DetailedToken(surface='会', tag='名詞-普通名詞-一般', inf='', lemma='会', reading='カイ', sub_tokens=None),
|
||||
], [
|
||||
DetailedToken(surface='選挙', tag='名詞-普通名詞-サ変可能', inf='', lemma='選挙', reading='センキョ', sub_tokens=None),
|
||||
DetailedToken(surface='管理', tag='名詞-普通名詞-サ変可能', inf='', lemma='管理', reading='カンリ', sub_tokens=None),
|
||||
DetailedToken(surface='委員会', tag='名詞-普通名詞-一般', inf='', lemma='委員会', reading='イインカイ', sub_tokens=None),
|
||||
]
|
||||
]]
|
||||
),
|
||||
]
|
||||
)
|
||||
def test_ja_tokenizer_sub_tokens(ja_tokenizer, text, sub_tokens_list_a, sub_tokens_list_b, sub_tokens_list_c):
|
||||
nlp_a = Japanese(meta={"tokenizer": {"config": {"split_mode": "A"}}})
|
||||
nlp_b = Japanese(meta={"tokenizer": {"config": {"split_mode": "B"}}})
|
||||
nlp_c = Japanese(meta={"tokenizer": {"config": {"split_mode": "C"}}})
|
||||
|
||||
assert ja_tokenizer(text).user_data["sub_tokens"] == sub_tokens_list_a
|
||||
assert nlp_a(text).user_data["sub_tokens"] == sub_tokens_list_a
|
||||
assert nlp_b(text).user_data["sub_tokens"] == sub_tokens_list_b
|
||||
assert nlp_c(text).user_data["sub_tokens"] == sub_tokens_list_c
|
||||
|
||||
|
||||
@pytest.mark.parametrize("text,inflections,reading_forms",
|
||||
[
|
||||
(
|
||||
"取ってつけた",
|
||||
("五段-ラ行,連用形-促音便", "", "下一段-カ行,連用形-一般", "助動詞-タ,終止形-一般"),
|
||||
("トッ", "テ", "ツケ", "タ"),
|
||||
),
|
||||
]
|
||||
)
|
||||
def test_ja_tokenizer_inflections_reading_forms(ja_tokenizer, text, inflections, reading_forms):
|
||||
assert ja_tokenizer(text).user_data["inflections"] == inflections
|
||||
assert ja_tokenizer(text).user_data["reading_forms"] == reading_forms
|
||||
|
||||
|
||||
def test_ja_tokenizer_emptyish_texts(ja_tokenizer):
|
||||
doc = ja_tokenizer("")
|
||||
assert len(doc) == 0
|
||||
|
|
|
|||
0
spacy/tests/lang/ne/__init__.py
Normal file
0
spacy/tests/lang/ne/__init__.py
Normal file
19
spacy/tests/lang/ne/test_text.py
Normal file
19
spacy/tests/lang/ne/test_text.py
Normal file
|
|
@ -0,0 +1,19 @@
|
|||
# coding: utf-8
|
||||
from __future__ import unicode_literals
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
def test_ne_tokenizer_handlers_long_text(ne_tokenizer):
|
||||
text = """मैले पाएको सर्टिफिकेटलाई म त बोक्रो सम्झन्छु र अभ्यास तब सुरु भयो, जब मैले कलेज पार गरेँ र जीवनको पढाइ सुरु गरेँ ।"""
|
||||
tokens = ne_tokenizer(text)
|
||||
assert len(tokens) == 24
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"text,length",
|
||||
[("समय जान कति पनि बेर लाग्दैन ।", 7), ("म ठूलो हुँदै थिएँ ।", 5)],
|
||||
)
|
||||
def test_ne_tokenizer_handles_cnts(ne_tokenizer, text, length):
|
||||
tokens = ne_tokenizer(text)
|
||||
assert len(tokens) == length
|
||||
|
|
@ -4,7 +4,9 @@ from spacy import util
|
|||
from spacy.gold import Example
|
||||
from spacy.lang.en import English
|
||||
from spacy.language import Language
|
||||
from spacy.tests.util import make_tempdir
|
||||
from spacy.symbols import POS, NOUN
|
||||
|
||||
from ..util import make_tempdir
|
||||
|
||||
|
||||
def test_label_types():
|
||||
|
|
@ -15,6 +17,19 @@ def test_label_types():
|
|||
nlp.get_pipe("tagger").add_label(9)
|
||||
|
||||
|
||||
def test_tagger_begin_training_tag_map():
|
||||
"""Test that Tagger.begin_training() without gold tuples does not clobber
|
||||
the tag map."""
|
||||
nlp = Language()
|
||||
tagger = nlp.create_pipe("tagger")
|
||||
orig_tag_count = len(tagger.labels)
|
||||
tagger.add_label("A", {"POS": "NOUN"})
|
||||
nlp.add_pipe(tagger)
|
||||
nlp.begin_training()
|
||||
assert nlp.vocab.morphology.tag_map["A"] == {POS: NOUN}
|
||||
assert orig_tag_count + 1 == len(nlp.get_pipe("tagger").labels)
|
||||
|
||||
|
||||
TAG_MAP = {"N": {"pos": "NOUN"}, "V": {"pos": "VERB"}, "J": {"pos": "ADJ"}}
|
||||
|
||||
MORPH_RULES = {"V": {"like": {"lemma": "luck"}}}
|
||||
|
|
|
|||
|
|
@ -11,6 +11,7 @@ from spacy.lang.en import English
|
|||
from spacy.lemmatizer import Lemmatizer
|
||||
from spacy.lookups import Lookups
|
||||
from spacy.tokens import Doc, Span
|
||||
from spacy.lang.en import EnglishDefaults
|
||||
|
||||
from ..util import get_doc, make_tempdir
|
||||
|
||||
|
|
@ -164,7 +165,7 @@ def test_issue595():
|
|||
lookups.add_table("lemma_rules", {"verb": [["ed", "e"]]})
|
||||
lookups.add_table("lemma_index", {"verb": {}})
|
||||
lookups.add_table("lemma_exc", {"verb": {}})
|
||||
lemmatizer = Lemmatizer(lookups)
|
||||
lemmatizer = Lemmatizer(lookups, is_base_form=EnglishDefaults.is_base_form)
|
||||
vocab = Vocab(lemmatizer=lemmatizer, tag_map=tag_map)
|
||||
doc = Doc(vocab, words=words)
|
||||
doc[2].tag_ = "VB"
|
||||
|
|
|
|||
|
|
@ -57,7 +57,7 @@ def test_issue2626_2835(en_tokenizer, text):
|
|||
|
||||
|
||||
def test_issue2656(en_tokenizer):
|
||||
"""Test that tokenizer correctly splits of punctuation after numbers with
|
||||
"""Test that tokenizer correctly splits off punctuation after numbers with
|
||||
decimal points.
|
||||
"""
|
||||
doc = en_tokenizer("I went for 40.3, and got home by 10.0.")
|
||||
|
|
|
|||
|
|
@ -2,6 +2,7 @@ import pytest
|
|||
from spacy.tokens import Doc
|
||||
from spacy.language import Language
|
||||
from spacy.lookups import Lookups
|
||||
from spacy.lemmatizer import Lemmatizer
|
||||
|
||||
|
||||
def test_lemmatizer_reflects_lookups_changes():
|
||||
|
|
@ -46,3 +47,14 @@ def test_tagger_warns_no_lookups():
|
|||
with pytest.warns(None) as record:
|
||||
nlp.begin_training()
|
||||
assert not record.list
|
||||
|
||||
|
||||
def test_lemmatizer_without_is_base_form_implementation():
|
||||
# Norwegian example from #5658
|
||||
lookups = Lookups()
|
||||
lookups.add_table("lemma_rules", {"noun": []})
|
||||
lookups.add_table("lemma_index", {"noun": {}})
|
||||
lookups.add_table("lemma_exc", {"noun": {"formuesskatten": ["formuesskatt"]}})
|
||||
|
||||
lemmatizer = Lemmatizer(lookups, is_base_form=None)
|
||||
assert lemmatizer("Formuesskatten", "noun", {'Definite': 'def', 'Gender': 'masc', 'Number': 'sing'}) == ["formuesskatt"]
|
||||
|
|
|
|||
|
|
@ -370,6 +370,6 @@ def test_vector_is_oov():
|
|||
data[1] = 2.0
|
||||
vocab.set_vector("cat", data[0])
|
||||
vocab.set_vector("dog", data[1])
|
||||
assert vocab["cat"].is_oov is True
|
||||
assert vocab["dog"].is_oov is True
|
||||
assert vocab["hamster"].is_oov is False
|
||||
assert vocab["cat"].is_oov is False
|
||||
assert vocab["dog"].is_oov is False
|
||||
assert vocab["hamster"].is_oov is True
|
||||
|
|
|
|||
|
|
@ -1062,7 +1062,7 @@ cdef class Doc:
|
|||
|
||||
DOCS: https://spacy.io/api/doc#to_bytes
|
||||
"""
|
||||
array_head = [LENGTH, SPACY, LEMMA, ENT_IOB, ENT_TYPE, ENT_ID, NORM] # TODO: ENT_KB_ID ?
|
||||
array_head = [LENGTH, SPACY, LEMMA, ENT_IOB, ENT_TYPE, ENT_ID, NORM, ENT_KB_ID]
|
||||
if self.is_tagged:
|
||||
array_head.extend([TAG, POS])
|
||||
# If doc parsed add head and dep attribute
|
||||
|
|
@ -1071,6 +1071,14 @@ cdef class Doc:
|
|||
# Otherwise add sent_start
|
||||
else:
|
||||
array_head.append(SENT_START)
|
||||
strings = set()
|
||||
for token in self:
|
||||
strings.add(token.tag_)
|
||||
strings.add(token.lemma_)
|
||||
strings.add(token.dep_)
|
||||
strings.add(token.ent_type_)
|
||||
strings.add(token.ent_kb_id_)
|
||||
strings.add(token.norm_)
|
||||
# Msgpack doesn't distinguish between lists and tuples, which is
|
||||
# vexing for user data. As a best guess, we *know* that within
|
||||
# keys, we must have tuples. In values we just have to hope
|
||||
|
|
@ -1082,6 +1090,7 @@ cdef class Doc:
|
|||
"sentiment": lambda: self.sentiment,
|
||||
"tensor": lambda: self.tensor,
|
||||
"cats": lambda: self.cats,
|
||||
"strings": lambda: list(strings),
|
||||
"has_unknown_spaces": lambda: self.has_unknown_spaces
|
||||
}
|
||||
if "user_data" not in exclude and self.user_data:
|
||||
|
|
@ -1110,6 +1119,7 @@ cdef class Doc:
|
|||
"sentiment": lambda b: None,
|
||||
"tensor": lambda b: None,
|
||||
"cats": lambda b: None,
|
||||
"strings": lambda b: None,
|
||||
"user_data_keys": lambda b: None,
|
||||
"user_data_values": lambda b: None,
|
||||
"has_unknown_spaces": lambda b: None
|
||||
|
|
@ -1130,6 +1140,9 @@ cdef class Doc:
|
|||
self.tensor = msg["tensor"]
|
||||
if "cats" not in exclude and "cats" in msg:
|
||||
self.cats = msg["cats"]
|
||||
if "strings" not in exclude and "strings" in msg:
|
||||
for s in msg["strings"]:
|
||||
self.vocab.strings.add(s)
|
||||
if "has_unknown_spaces" not in exclude and "has_unknown_spaces" in msg:
|
||||
self.has_unknown_spaces = msg["has_unknown_spaces"]
|
||||
start = 0
|
||||
|
|
|
|||
|
|
@ -923,7 +923,7 @@ cdef class Token:
|
|||
@property
|
||||
def is_oov(self):
|
||||
"""RETURNS (bool): Whether the token is out-of-vocabulary."""
|
||||
return self.c.lex.orth in self.vocab.vectors
|
||||
return self.c.lex.orth not in self.vocab.vectors
|
||||
|
||||
@property
|
||||
def is_stop(self):
|
||||
|
|
|
|||
|
|
@ -187,6 +187,10 @@ def load_model_from_path(model_path, meta=False, **overrides):
|
|||
pipeline = nlp.Defaults.pipe_names
|
||||
elif pipeline in (False, None):
|
||||
pipeline = []
|
||||
# skip "vocab" from overrides in component initialization since vocab is
|
||||
# already configured from overrides when nlp is initialized above
|
||||
if "vocab" in overrides:
|
||||
del overrides["vocab"]
|
||||
for name in pipeline:
|
||||
if name not in disable:
|
||||
config = meta.get("pipeline_args", {}).get(name, {})
|
||||
|
|
|
|||
|
|
@ -105,8 +105,8 @@ The Chinese language class supports three word segmentation options:
|
|||
> ```
|
||||
|
||||
1. **Character segmentation:** Character segmentation is the default
|
||||
segmentation option. It's enabled when you create a new `Chinese`
|
||||
language class or call `spacy.blank("zh")`.
|
||||
segmentation option. It's enabled when you create a new `Chinese` language
|
||||
class or call `spacy.blank("zh")`.
|
||||
2. **Jieba:** `Chinese` uses [Jieba](https://github.com/fxsjy/jieba) for word
|
||||
segmentation with the tokenizer option `{"segmenter": "jieba"}`.
|
||||
3. **PKUSeg**: As of spaCy v2.3.0, support for
|
||||
|
|
|
|||
|
|
@ -1,5 +1,58 @@
|
|||
{
|
||||
"resources": [
|
||||
{
|
||||
"id": "spacy-streamlit",
|
||||
"title": "spacy-streamlit",
|
||||
"slogan": "spaCy building blocks for Streamlit apps",
|
||||
"github": "explosion/spacy-streamlit",
|
||||
"description": "This package contains utilities for visualizing spaCy models and building interactive spaCy-powered apps with [Streamlit](https://streamlit.io). It includes various building blocks you can use in your own Streamlit app, like visualizers for **syntactic dependencies**, **named entities**, **text classification**, **semantic similarity** via word vectors, token attributes, and more.",
|
||||
"pip": "spacy-streamlit",
|
||||
"category": ["visualizers"],
|
||||
"thumb": "https://i.imgur.com/mhEjluE.jpg",
|
||||
"image": "https://user-images.githubusercontent.com/13643239/85388081-f2da8700-b545-11ea-9bd4-e303d3c5763c.png",
|
||||
"code_example": [
|
||||
"import spacy_streamlit",
|
||||
"",
|
||||
"models = [\"en_core_web_sm\", \"en_core_web_md\"]",
|
||||
"default_text = \"Sundar Pichai is the CEO of Google.\"",
|
||||
"spacy_streamlit.visualize(models, default_text))"
|
||||
],
|
||||
"author": "Ines Montani",
|
||||
"author_links": {
|
||||
"twitter": "_inesmontani",
|
||||
"github": "ines",
|
||||
"website": "https://ines.io"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "spaczz",
|
||||
"title": "spaczz",
|
||||
"slogan": "Fuzzy matching and more for spaCy.",
|
||||
"description": "Spaczz provides fuzzy matching and multi-token regex matching functionality for spaCy. Spaczz's components have similar APIs to their spaCy counterparts and spaczz pipeline components can integrate into spaCy pipelines where they can be saved/loaded as models.",
|
||||
"github": "gandersen101/spaczz",
|
||||
"pip": "spaczz",
|
||||
"code_example": [
|
||||
"import spacy",
|
||||
"from spaczz.pipeline import SpaczzRuler",
|
||||
"",
|
||||
"nlp = spacy.blank('en')",
|
||||
"ruler = SpaczzRuler(nlp)",
|
||||
"ruler.add_patterns([{'label': 'PERSON', 'pattern': 'Bill Gates', 'type': 'fuzzy'}])",
|
||||
"nlp.add_pipe(ruler)",
|
||||
"",
|
||||
"doc = nlp('Oops, I spelled Bill Gatez wrong.')",
|
||||
"print([(ent.text, ent.start, ent.end, ent.label_) for ent in doc.ents])"
|
||||
],
|
||||
"code_language": "python",
|
||||
"url": "https://spaczz.readthedocs.io/en/latest/",
|
||||
"author": "Grant Andersen",
|
||||
"author_links": {
|
||||
"twitter": "gandersen101",
|
||||
"github": "gandersen101"
|
||||
},
|
||||
"category": ["pipeline"],
|
||||
"tags": ["fuzzy-matching", "regex"]
|
||||
},
|
||||
{
|
||||
"id": "spacy-universal-sentence-encoder",
|
||||
"title": "SpaCy - Universal Sentence Encoder",
|
||||
|
|
@ -1238,6 +1291,19 @@
|
|||
"youtube": "K1elwpgDdls",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-spacy-course-es",
|
||||
"title": "NLP avanzado con spaCy · Un curso en línea gratis",
|
||||
"description": "spaCy es un paquete moderno de Python para hacer Procesamiento de Lenguaje Natural de potencia industrial. En este curso en línea, interactivo y gratuito, aprenderás a usar spaCy para construir sistemas avanzados de comprensión de lenguaje natural usando enfoques basados en reglas y en machine learning.",
|
||||
"url": "https://course.spacy.io/es",
|
||||
"author": "Camila Gutiérrez",
|
||||
"author_links": {
|
||||
"twitter": "Mariacamilagl30"
|
||||
},
|
||||
"youtube": "RNiLVCE5d4k",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-intro-to-nlp-episode-1",
|
||||
|
|
@ -1294,6 +1360,20 @@
|
|||
"youtube": "IqOJU1-_Fi0",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-intro-to-nlp-episode-5",
|
||||
"title": "Intro to NLP with spaCy (5)",
|
||||
"slogan": "Episode 5: Rules vs. Machine Learning",
|
||||
"description": "In this new video series, data science instructor Vincent Warmerdam gets started with spaCy, an open-source library for Natural Language Processing in Python. His mission: building a system to automatically detect programming languages in large volumes of text. Follow his process from the first idea to a prototype all the way to data collection and training a statistical named entity recogntion model from scratch.",
|
||||
"author": "Vincent Warmerdam",
|
||||
"author_links": {
|
||||
"twitter": "fishnets88",
|
||||
"github": "koaning"
|
||||
},
|
||||
"youtube": "f4sqeLRzkPg",
|
||||
"category": ["videos"]
|
||||
},
|
||||
{
|
||||
"type": "education",
|
||||
"id": "video-spacy-irl-entity-linking",
|
||||
|
|
@ -2348,6 +2428,56 @@
|
|||
},
|
||||
"category": ["pipeline", "conversational", "research"],
|
||||
"tags": ["spell check", "correction", "preprocessing", "translation", "correction"]
|
||||
},
|
||||
{
|
||||
"id": "texthero",
|
||||
"title": "Texthero",
|
||||
"slogan": "Text preprocessing, representation and visualization from zero to hero.",
|
||||
"description": "Texthero is a python package to work with text data efficiently. It empowers NLP developers with a tool to quickly understand any text-based dataset and it provides a solid pipeline to clean and represent text data, from zero to hero.",
|
||||
"github": "jbesomi/texthero",
|
||||
"pip": "texthero",
|
||||
"code_example": [
|
||||
"import texthero as hero",
|
||||
"import pandas as pd",
|
||||
"",
|
||||
"df = pd.read_csv('https://github.com/jbesomi/texthero/raw/master/dataset/bbcsport.csv')",
|
||||
"df['named_entities'] = hero.named_entities(df['text'])",
|
||||
"df.head()"
|
||||
],
|
||||
"code_language": "python",
|
||||
"url": "https://texthero.org",
|
||||
"thumb": "https://texthero.org/img/T.png",
|
||||
"image": "https://texthero.org/docs/assets/texthero.png",
|
||||
"author": "Jonathan Besomi",
|
||||
"author_links": {
|
||||
"github": "jbesomi",
|
||||
"website": "https://besomi.ai"
|
||||
},
|
||||
"category": ["standalone"]
|
||||
},
|
||||
{
|
||||
"id": "cov-bsv",
|
||||
"title": "VA COVID-19 NLP BSV",
|
||||
"slogan": "spaCy pipeline for COVID-19 surveillance.",
|
||||
"github": "abchapman93/VA_COVID-19_NLP_BSV",
|
||||
"description": "A spaCy rule-based pipeline for identifying positive cases of COVID-19 from clinical text. A version of this system was deployed as part of the US Department of Veterans Affairs biosurveillance response to COVID-19.",
|
||||
"pip": "cov-bsv",
|
||||
"code_example": [
|
||||
"import cov_bsv",
|
||||
"",
|
||||
"nlp = cov_bsv.load()",
|
||||
"text = 'Pt tested for COVID-19. His wife was recently diagnosed with novel coronavirus. SARS-COV-2: Detected'",
|
||||
"",
|
||||
"print(doc.ents)",
|
||||
"print(doc._.cov_classification)",
|
||||
"cov_bsv.visualize_doc(doc)"
|
||||
],
|
||||
"category": ["pipeline", "standalone", "biomedical", "scientific"],
|
||||
"tags": ["clinical", "epidemiology", "covid-19", "surveillance"],
|
||||
"author": "Alec Chapman",
|
||||
"author_links": {
|
||||
"github": "abchapman93"
|
||||
}
|
||||
}
|
||||
],
|
||||
|
||||
|
|
|
|||
56916
website/package-lock.json
generated
56916
website/package-lock.json
generated
File diff suppressed because it is too large
Load Diff
Loading…
Reference in New Issue
Block a user