diff --git a/.github/contributors/delzac.md b/.github/contributors/delzac.md new file mode 100644 index 000000000..0fcfe6f2f --- /dev/null +++ b/.github/contributors/delzac.md @@ -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 | Matthew Chin | +| Company name (if applicable) | | +| Title or role (if applicable) | | +| Date | 2020-09-22 | +| GitHub username | delzac | +| Website (optional) | | diff --git a/.github/contributors/florijanstamenkovic.md b/.github/contributors/florijanstamenkovic.md new file mode 100644 index 000000000..65da875b1 --- /dev/null +++ b/.github/contributors/florijanstamenkovic.md @@ -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 | Florijan Stamenkovic | +| Company name (if applicable) | | +| Title or role (if applicable) | | +| Date | 2020-10-05 | +| GitHub username | florijanstamenkovic | +| Website (optional) | | diff --git a/.github/contributors/zaibacu.md b/.github/contributors/zaibacu.md new file mode 100644 index 000000000..365b89848 --- /dev/null +++ b/.github/contributors/zaibacu.md @@ -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 | Šarūnas Navickas | +| Company name (if applicable) | TokenMill | +| Title or role (if applicable) | Data Engineer | +| Date | 2020-09-24 | +| GitHub username | zaibacu | +| Website (optional) | | diff --git a/spacy/lang/tr/__init__.py b/spacy/lang/tr/__init__.py index 8bd0b93df..788adb6fb 100644 --- a/spacy/lang/tr/__init__.py +++ b/spacy/lang/tr/__init__.py @@ -1,5 +1,6 @@ from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS from .stop_words import STOP_WORDS +from .syntax_iterators import SYNTAX_ITERATORS from .lex_attrs import LEX_ATTRS from ...language import Language @@ -8,6 +9,7 @@ class TurkishDefaults(Language.Defaults): tokenizer_exceptions = TOKENIZER_EXCEPTIONS lex_attr_getters = LEX_ATTRS stop_words = STOP_WORDS + syntax_iterators = SYNTAX_ITERATORS class Turkish(Language): diff --git a/spacy/lang/tr/lex_attrs.py b/spacy/lang/tr/lex_attrs.py index 3dbc1833a..3615f4b4c 100644 --- a/spacy/lang/tr/lex_attrs.py +++ b/spacy/lang/tr/lex_attrs.py @@ -32,6 +32,36 @@ _num_words = [ ] +_ordinal_words = [ + "birinci", + "ikinci", + "üçüncü", + "dördüncü", + "beşinci", + "altıncı", + "yedinci", + "sekizinci", + "dokuzuncu", + "onuncu", + "yirminci", + "otuzuncu", + "kırkıncı", + "ellinci", + "altmışıncı", + "yetmişinci", + "sekseninci", + "doksanıncı", + "yüzüncü", + "bininci", + "mliyonuncu", + "milyarıncı", + "trilyonuncu", + "katrilyonuncu", + "kentilyonuncu", +] + +_ordinal_endings = ("inci", "ıncı", "nci", "ncı", "uncu", "üncü") + def like_num(text): if text.startswith(("+", "-", "±", "~")): text = text[1:] @@ -42,8 +72,20 @@ def like_num(text): num, denom = text.split("/") if num.isdigit() and denom.isdigit(): return True - if text.lower() in _num_words: + + text_lower = text.lower() + + #Check cardinal number + if text_lower in _num_words: return True + + #Check ordinal number + if text_lower in _ordinal_words: + return True + if text_lower.endswith(_ordinal_endings): + if text_lower[:-3].isdigit() or text_lower[:-4].isdigit(): + return True + return False diff --git a/spacy/lang/tr/syntax_iterators.py b/spacy/lang/tr/syntax_iterators.py new file mode 100644 index 000000000..665ccb590 --- /dev/null +++ b/spacy/lang/tr/syntax_iterators.py @@ -0,0 +1,59 @@ +# coding: utf8 +from __future__ import unicode_literals + +from ...symbols import NOUN, PROPN, PRON +from ...errors import Errors + + +def noun_chunks(doclike): + """ + Detect base noun phrases from a dependency parse. Works on both Doc and Span. + """ + # Please see documentation for Turkish NP structure + labels = [ + "nsubj", + "iobj", + "obj", + "obl", + "appos", + "orphan", + "dislocated", + "ROOT", + ] + doc = doclike.doc # Ensure works on both Doc and Span. + if not doc.has_annotation("DEP"): + raise ValueError(Errors.E029) + + np_deps = [doc.vocab.strings.add(label) for label in labels] + conj = doc.vocab.strings.add("conj") + flat = doc.vocab.strings.add("flat") + np_label = doc.vocab.strings.add("NP") + + def extend_right(w): # Playing a trick for flat + rindex = w.i + 1 + for rdep in doc[w.i].rights: # Extend the span to right if there is a flat + if rdep.dep == flat and rdep.pos in (NOUN, PROPN): + rindex = rdep.i + 1 + else: + break + return rindex + + prev_end = len(doc) + 1 + for i, word in reversed(list(enumerate(doclike))): + if word.pos not in (NOUN, PROPN, PRON): + continue + # Prevent nested chunks from being produced + if word.i >= prev_end: + continue + if word.dep in np_deps: + prev_end = word.left_edge.i + yield word.left_edge.i, extend_right(word), np_label + elif word.dep == conj: + cc_token = word.left_edge + prev_end = cc_token.i + yield cc_token.right_edge.i + 1, extend_right(word), np_label # Shave off cc tokens from the NP + + + + +SYNTAX_ITERATORS = {"noun_chunks": noun_chunks} diff --git a/spacy/tests/conftest.py b/spacy/tests/conftest.py index 411397b42..7f8ab6768 100644 --- a/spacy/tests/conftest.py +++ b/spacy/tests/conftest.py @@ -239,6 +239,9 @@ def th_tokenizer(): def tr_tokenizer(): return get_lang_class("tr")().tokenizer +@pytest.fixture(scope="session") +def tr_vocab(): + return get_lang_class("tr").Defaults.create_vocab() @pytest.fixture(scope="session") def tt_tokenizer(): diff --git a/spacy/tests/lang/tr/test_noun_chunks.py b/spacy/tests/lang/tr/test_noun_chunks.py new file mode 100644 index 000000000..003e4f08e --- /dev/null +++ b/spacy/tests/lang/tr/test_noun_chunks.py @@ -0,0 +1,12 @@ +import pytest + + +def test_noun_chunks_is_parsed(tr_tokenizer): + """Test that noun_chunks raises Value Error for 'tr' language if Doc is not parsed. + To check this test, we're constructing a Doc + with a new Vocab here and forcing is_parsed to 'False' + to make sure the noun chunks don't run. + """ + doc = tr_tokenizer("Dün seni gördüm.") + with pytest.raises(ValueError): + list(doc.noun_chunks) diff --git a/spacy/tests/lang/tr/test_parser.py b/spacy/tests/lang/tr/test_parser.py new file mode 100644 index 000000000..ff71ac3d4 --- /dev/null +++ b/spacy/tests/lang/tr/test_parser.py @@ -0,0 +1,570 @@ +from spacy.tokens import Doc + + +def test_tr_noun_chunks_amod_simple(tr_tokenizer): + text = "sarı kedi" + heads = [1, 1] + deps = ["amod", "ROOT"] + pos = ["ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "sarı kedi " + + +def test_tr_noun_chunks_nmod_simple(tr_tokenizer): + text = "arkadaşımın kedisi" # my friend's cat + heads = [1, 1] + deps = ["nmod", "ROOT"] + pos = ["NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "arkadaşımın kedisi " + + +def test_tr_noun_chunks_determiner_simple(tr_tokenizer): + text = "O kedi" # that cat + heads = [1, 1] + deps = ["det", "ROOT"] + pos = ["DET", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "O kedi " + + +def test_tr_noun_chunks_nmod_amod(tr_tokenizer): + text = "okulun eski müdürü" + heads = [2, 2, 2] + deps = ["nmod", "amod", "ROOT"] + pos = ["NOUN", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "okulun eski müdürü " + + +def test_tr_noun_chunks_one_det_one_adj_simple(tr_tokenizer): + text = "O sarı kedi" + heads = [2, 2, 2] + deps = ["det", "amod", "ROOT"] + pos = ["DET", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "O sarı kedi " + + +def test_tr_noun_chunks_two_adjs_simple(tr_tokenizer): + text = "beyaz tombik kedi" + heads = [2, 2, 2] + deps = ["amod", "amod", "ROOT"] + pos = ["ADJ", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "beyaz tombik kedi " + + +def test_tr_noun_chunks_one_det_two_adjs_simple(tr_tokenizer): + text = "o beyaz tombik kedi" + heads = [3, 3, 3, 3] + deps = ["det", "amod", "amod", "ROOT"] + pos = ["DET", "ADJ", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "o beyaz tombik kedi " + + +def test_tr_noun_chunks_nmod_two(tr_tokenizer): + text = "kızın saçının rengi" + heads = [1, 2, 2] + deps = ["nmod", "nmod", "ROOT"] + pos = ["NOUN", "NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "kızın saçının rengi " + + +def test_tr_noun_chunks_chain_nmod_with_adj(tr_tokenizer): + text = "ev sahibinin tatlı köpeği" + heads = [1, 3, 3, 3] + deps = ["nmod", "nmod", "amod", "ROOT"] + pos = ["NOUN", "NOUN", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "ev sahibinin tatlı köpeği " + + +def test_tr_noun_chunks_chain_nmod_with_acl(tr_tokenizer): + text = "ev sahibinin gelen köpeği" + heads = [1, 3, 3, 3] + deps = ["nmod", "nmod", "acl", "ROOT"] + pos = ["NOUN", "NOUN", "VERB", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "ev sahibinin gelen köpeği " + + +def test_tr_noun_chunks_chain_nmod_head_with_amod_acl(tr_tokenizer): + text = "arabanın kırdığım sol aynası" + heads = [3, 3, 3, 3] + deps = ["nmod", "acl", "amod", "ROOT"] + pos = ["NOUN", "VERB", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "arabanın kırdığım sol aynası " + + +def test_tr_noun_chunks_nmod_three(tr_tokenizer): + text = "güney Afrika ülkelerinden Mozambik" + heads = [1, 2, 3, 3] + deps = ["nmod", "nmod", "nmod", "ROOT"] + pos = ["NOUN", "PROPN", "NOUN", "PROPN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "güney Afrika ülkelerinden Mozambik " + + +def test_tr_noun_chunks_det_amod_nmod(tr_tokenizer): + text = "bazı eski oyun kuralları" + heads = [3, 3, 3, 3] + deps = ["det", "nmod", "nmod", "ROOT"] + pos = ["DET", "ADJ", "NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "bazı eski oyun kuralları " + + +def test_tr_noun_chunks_acl_simple(tr_tokenizer): + text = "bahçesi olan okul" + heads = [2, 0, 2] + deps = ["acl", "cop", "ROOT"] + pos = ["NOUN", "AUX", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "bahçesi olan okul " + + +def test_tr_noun_chunks_acl_verb(tr_tokenizer): + text = "sevdiğim sanatçılar" + heads = [1, 1] + deps = ["acl", "ROOT"] + pos = ["VERB", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "sevdiğim sanatçılar " + + +def test_tr_noun_chunks_acl_nmod(tr_tokenizer): + text = "en sevdiğim ses sanatçısı" + heads = [1, 3, 3, 3] + deps = ["advmod", "acl", "nmod", "ROOT"] + pos = ["ADV", "VERB", "NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "en sevdiğim ses sanatçısı " + + +def test_tr_noun_chunks_acl_nmod(tr_tokenizer): + text = "bildiğim bir turizm şirketi" + heads = [3, 3, 3, 3] + deps = ["acl", "det", "nmod", "ROOT"] + pos = ["VERB", "DET", "NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "bildiğim bir turizm şirketi " + + +def test_tr_noun_chunks_np_recursive_nsubj_to_root(tr_tokenizer): + text = "Simge'nin okuduğu kitap" + heads = [1, 2, 2] + deps = ["nsubj", "acl", "ROOT"] + pos = ["PROPN", "VERB", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Simge'nin okuduğu kitap " + + +def test_tr_noun_chunks_np_recursive_nsubj_attached_to_pron_root(tr_tokenizer): + text = "Simge'nin konuşabileceği birisi" + heads = [1, 2, 2] + deps = ["nsubj", "acl", "ROOT"] + pos = ["PROPN", "VERB", "PRON"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Simge'nin konuşabileceği birisi " + + +def test_tr_noun_chunks_np_recursive_nsubj_in_subnp(tr_tokenizer): + text = "Simge'nin yarın gideceği yer" + heads = [2, 2, 3, 3] + deps = ["nsubj", "obl", "acl", "ROOT"] + pos = ["PROPN", "NOUN", "VERB", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Simge'nin yarın gideceği yer " + + +def test_tr_noun_chunks_np_recursive_two_nmods(tr_tokenizer): + text = "ustanın kapısını degiştireceği çamasır makinası" + heads = [2, 2, 4, 4, 4] + deps = ["nsubj", "obj", "acl", "nmod", "ROOT"] + pos = ["NOUN", "NOUN", "VERB", "NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "ustanın kapısını degiştireceği çamasır makinası " + + +def test_tr_noun_chunks_np_recursive_four_nouns(tr_tokenizer): + text = "kızına piyano dersi verdiğim hanım" + heads = [3, 2, 3, 4, 4] + deps = ["obl", "nmod", "obj", "acl", "ROOT"] + pos = ["NOUN", "NOUN", "NOUN", "VERB", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "kızına piyano dersi verdiğim hanım " + + +def test_tr_noun_chunks_np_recursive_no_nmod(tr_tokenizer): + text = "içine birkaç çiçek konmuş olan bir vazo" + heads = [3, 2, 3, 6, 3, 6, 6] + deps = ["obl", "det", "nsubj", "acl", "aux", "det", "ROOT"] + pos = ["ADP", "DET", "NOUN", "VERB", "AUX", "DET", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "içine birkaç çiçek konmuş olan bir vazo " + + +def test_tr_noun_chunks_np_recursive_long_two_acls(tr_tokenizer): + text = "içine Simge'nin bahçesinden toplanmış birkaç çiçeğin konmuş olduğu bir vazo" + heads = [6, 2, 3, 5, 5, 6, 9, 6, 9, 9] + deps = ["obl", "nmod" , "obl", "acl", "det", "nsubj", "acl", "aux", "det", "ROOT"] + pos = ["ADP", "PROPN", "NOUN", "VERB", "DET", "NOUN", "VERB", "AUX", "DET", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "içine Simge'nin bahçesinden toplanmış birkaç çiçeğin konmuş olduğu bir vazo " + + +def test_tr_noun_chunks_two_nouns_in_nmod(tr_tokenizer): + text = "kız ve erkek çocuklar" + heads = [3, 2, 0, 3] + deps = ["nmod", "cc", "conj", "ROOT"] + pos = ["NOUN", "CCONJ", "NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "kız ve erkek çocuklar " + +def test_tr_noun_chunks_two_nouns_in_nmod(tr_tokenizer): + text = "tatlı ve gürbüz çocuklar" + heads = [3, 2, 0, 3] + deps = ["amod", "cc", "conj", "ROOT"] + pos = ["ADJ", "CCONJ", "NOUN", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "tatlı ve gürbüz çocuklar " + + +def test_tr_noun_chunks_conj_simple(tr_tokenizer): + text = "Sen ya da ben" + heads = [0, 3, 1, 0] + deps = ["ROOT", "cc", "fixed", "conj"] + pos = ["PRON", "CCONJ", "CCONJ", "PRON"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 2 + assert chunks[0].text_with_ws == "ben " + assert chunks[1].text_with_ws == "Sen " + +def test_tr_noun_chunks_conj_three(tr_tokenizer): + text = "sen, ben ve ondan" + heads = [0, 2, 0, 4, 0] + deps = ["ROOT", "punct", "conj", "cc", "conj"] + pos = ["PRON", "PUNCT", "PRON", "CCONJ", "PRON"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 3 + assert chunks[0].text_with_ws == "ondan " + assert chunks[1].text_with_ws == "ben " + assert chunks[2].text_with_ws == "sen " + + +def test_tr_noun_chunks_conj_three(tr_tokenizer): + text = "ben ya da sen ya da onlar" + heads = [0, 3, 1, 0, 6, 4, 3] + deps = ["ROOT", "cc", "fixed", "conj", "cc", "fixed", "conj"] + pos = ["PRON", "CCONJ", "CCONJ", "PRON", "CCONJ", "CCONJ", "PRON"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 3 + assert chunks[0].text_with_ws == "onlar " + assert chunks[1].text_with_ws == "sen " + assert chunks[2].text_with_ws == "ben " + + +def test_tr_noun_chunks_conj_and_adj_phrase(tr_tokenizer): + text = "ben ve akıllı çocuk" + heads = [0, 3, 3, 0] + deps = ["ROOT", "cc", "amod", "conj"] + pos = ["PRON", "CCONJ", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 2 + assert chunks[0].text_with_ws == "akıllı çocuk " + assert chunks[1].text_with_ws == "ben " + + +def test_tr_noun_chunks_conj_fixed_adj_phrase(tr_tokenizer): + text = "ben ya da akıllı çocuk" + heads = [0, 4, 1, 4, 0] + deps = ["ROOT", "cc", "fixed", "amod", "conj"] + pos = ["PRON", "CCONJ", "CCONJ", "ADJ", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 2 + assert chunks[0].text_with_ws == "akıllı çocuk " + assert chunks[1].text_with_ws == "ben " + + +def test_tr_noun_chunks_conj_subject(tr_tokenizer): + text = "Sen ve ben iyi anlaşıyoruz" + heads = [4, 2, 0, 2, 4] + deps = ["nsubj", "cc", "conj", "adv", "ROOT"] + pos = ["PRON", "CCONJ", "PRON", "ADV", "VERB"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 2 + assert chunks[0].text_with_ws == "ben " + assert chunks[1].text_with_ws == "Sen " + + +def test_tr_noun_chunks_conj_noun_head_verb(tr_tokenizer): + text = "Simge babasını görmüyormuş, annesini değil" + heads = [2, 2, 2, 4, 2, 4] + deps = ["nsubj", "obj", "ROOT", "punct", "conj", "aux"] + pos = ["PROPN", "NOUN", "VERB", "PUNCT", "NOUN", "AUX"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 3 + assert chunks[0].text_with_ws == "annesini " + assert chunks[1].text_with_ws == "babasını " + assert chunks[2].text_with_ws == "Simge " + + +def test_tr_noun_chunks_flat_simple(tr_tokenizer): + text = "New York" + heads = [0, 0] + deps = ["ROOT", "flat"] + pos = ["PROPN", "PROPN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "New York " + + +def test_tr_noun_chunks_flat_names_and_title(tr_tokenizer): + text = "Gazi Mustafa Kemal" + heads = [1, 1, 1] + deps = ["nmod", "ROOT", "flat"] + pos = ["PROPN", "PROPN", "PROPN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Gazi Mustafa Kemal " + + +def test_tr_noun_chunks_flat_names_and_title(tr_tokenizer): + text = "Ahmet Vefik Paşa" + heads = [2, 0, 2] + deps = ["nmod", "flat", "ROOT"] + pos = ["PROPN", "PROPN", "PROPN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Ahmet Vefik Paşa " + + +def test_tr_noun_chunks_flat_name_lastname_and_title(tr_tokenizer): + text = "Cumhurbaşkanı Ahmet Necdet Sezer" + heads = [1, 1, 1, 1] + deps = ["nmod", "ROOT", "flat", "flat"] + pos = ["NOUN", "PROPN", "PROPN", "PROPN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Cumhurbaşkanı Ahmet Necdet Sezer " + + +def test_tr_noun_chunks_flat_in_nmod(tr_tokenizer): + text = "Ahmet Sezer adında bir ögrenci" + heads = [2, 0, 4, 4, 4] + deps = ["nmod", "flat", "nmod", "det", "ROOT"] + pos = ["PROPN", "PROPN", "NOUN", "DET", "NOUN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Ahmet Sezer adında bir ögrenci " + + +def test_tr_noun_chunks_flat_and_chain_nmod(tr_tokenizer): + text = "Batı Afrika ülkelerinden Sierra Leone" + heads = [1, 2, 3, 3, 3] + deps = ["nmod", "nmod", "nmod", "ROOT", "flat"] + pos = ["NOUN", "PROPN", "NOUN", "PROPN", "PROPN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 1 + assert chunks[0].text_with_ws == "Batı Afrika ülkelerinden Sierra Leone " + + +def test_tr_noun_chunks_two_flats_conjed(tr_tokenizer): + text = "New York ve Sierra Leone" + heads = [0, 0, 3, 0, 3] + deps = ["ROOT", "flat", "cc", "conj", "flat"] + pos = ["PROPN", "PROPN", "CCONJ", "PROPN", "PROPN"] + tokens = tr_tokenizer(text) + doc = Doc( + tokens.vocab, words=[t.text for t in tokens], pos=pos, heads=heads, deps=deps + ) + chunks = list(doc.noun_chunks) + assert len(chunks) == 2 + assert chunks[0].text_with_ws == "Sierra Leone " + assert chunks[1].text_with_ws == "New York " diff --git a/spacy/tests/lang/tr/test_text.py b/spacy/tests/lang/tr/test_text.py new file mode 100644 index 000000000..01e279d76 --- /dev/null +++ b/spacy/tests/lang/tr/test_text.py @@ -0,0 +1,29 @@ +import pytest +from spacy.lang.tr.lex_attrs import like_num + + +@pytest.mark.parametrize( + "word", + [ + "bir", + "iki", + "dört", + "altı", + "milyon", + "100", + "birinci", + "üçüncü", + "beşinci", + "100üncü", + "8inci" + ] +) +def test_tr_lex_attrs_like_number_cardinal_ordinal(word): + assert like_num(word) + + +@pytest.mark.parametrize("word", ["beş", "yedi", "yedinci", "birinci"]) +def test_tr_lex_attrs_capitals(word): + assert like_num(word) + assert like_num(word.upper()) + diff --git a/spacy/tests/regression/test_issue6207.py b/spacy/tests/regression/test_issue6207.py new file mode 100644 index 000000000..47e3803e9 --- /dev/null +++ b/spacy/tests/regression/test_issue6207.py @@ -0,0 +1,15 @@ +from spacy.util import filter_spans + + +def test_issue6207(en_tokenizer): + doc = en_tokenizer("zero one two three four five six") + + # Make spans + s1 = doc[:4] + s2 = doc[3:6] # overlaps with s1 + s3 = doc[5:7] # overlaps with s2, not s1 + + result = filter_spans((s1, s2, s3)) + assert s1 in result + assert s2 not in result + assert s3 in result diff --git a/spacy/util.py b/spacy/util.py index bf4ea0c92..3d567a425 100644 --- a/spacy/util.py +++ b/spacy/util.py @@ -1018,7 +1018,7 @@ def filter_spans(spans: Iterable["Span"]) -> List["Span"]: # Check for end - 1 here because boundaries are inclusive if span.start not in seen_tokens and span.end - 1 not in seen_tokens: result.append(span) - seen_tokens.update(range(span.start, span.end)) + seen_tokens.update(range(span.start, span.end)) result = sorted(result, key=lambda span: span.start) return result diff --git a/website/docs/usage/rule-based-matching.md b/website/docs/usage/rule-based-matching.md index 256f4ccb4..a510398e6 100644 --- a/website/docs/usage/rule-based-matching.md +++ b/website/docs/usage/rule-based-matching.md @@ -167,6 +167,7 @@ rule-based matching are: |  `IS_ALPHA`, `IS_ASCII`, `IS_DIGIT` | Token text consists of alphabetic characters, ASCII characters, digits. ~~bool~~ | |  `IS_LOWER`, `IS_UPPER`, `IS_TITLE` | Token text is in lowercase, uppercase, titlecase. ~~bool~~ | |  `IS_PUNCT`, `IS_SPACE`, `IS_STOP` | Token is punctuation, whitespace, stop word. ~~bool~~ | +|  `IS_SENT_START` | Token is start of sentence. ~~bool~~ | |  `LIKE_NUM`, `LIKE_URL`, `LIKE_EMAIL` | Token text resembles a number, URL, email. ~~bool~~ | |  `POS`, `TAG`, `MORPH`, `DEP`, `LEMMA`, `SHAPE` | The token's simple and extended part-of-speech tag, morphological analysis, dependency label, lemma, shape. ~~str~~ | | `ENT_TYPE` | The token's entity label. ~~str~~ | diff --git a/website/meta/universe.json b/website/meta/universe.json index 74c35bdb8..ffad74180 100644 --- a/website/meta/universe.json +++ b/website/meta/universe.json @@ -2542,6 +2542,42 @@ "author_links": { "github": "abchapman93" } + }, + { + "id": "rita-dsl", + "title": "RITA DSL", + "slogan": "Domain Specific Language for creating language rules", + "github": "zaibacu/rita-dsl", + "description": "A Domain Specific Language (DSL) for building language patterns. These can be later compiled into spaCy patterns, pure regex, or any other format", + "pip": "rita-dsl", + "thumb": "https://raw.githubusercontent.com/zaibacu/rita-dsl/master/docs/assets/logo-100px.png", + "code_language": "python", + "code_example": [ + "import spacy", + "from rita.shortcuts import setup_spacy", + "", + "rules = \"\"\"", + "cuts = {\"fitted\", \"wide-cut\"}", + "lengths = {\"short\", \"long\", \"calf-length\", \"knee-length\"}", + "fabric_types = {\"soft\", \"airy\", \"crinkled\"}", + "fabrics = {\"velour\", \"chiffon\", \"knit\", \"woven\", \"stretch\"}", + "", + "{IN_LIST(cuts)?, IN_LIST(lengths), WORD(\"dress\")}->MARK(\"DRESS_TYPE\")", + "{IN_LIST(lengths), IN_LIST(cuts), WORD(\"dress\")}->MARK(\"DRESS_TYPE\")", + "{IN_LIST(fabric_types)?, IN_LIST(fabrics)}->MARK(\"DRESS_FABRIC\")", + "\"\"\"", + "", + "nlp = spacy.load(\"en\")", + "setup_spacy(nlp, rules_string=rules)", + "r = nlp(\"She was wearing a short wide-cut dress\")", + "print(list([{\"label\": e.label_, \"text\": e.text} for e in r.ents]))" + ], + "category": ["standalone"], + "tags": ["dsl", "language-patterns", "language-rules", "nlp"], + "author": "Šarūnas Navickas", + "author_links": { + "github": "zaibacu" + } } ],