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Add optional id property to EntityRuler patterns (#3591)

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* Adding support for entity_id in EntityRuler pipeline component

* Adding Spacy Contributor aggreement

* Updating EntityRuler to use string.format instead of f strings

* Update Entity Ruler to support an 'id' attribute per pattern that explicitly identifies an entity.

* Fixing tests

* Remove custom extension entity_id and use built in ent_id token attribute.

* Changing entity_id to ent_id for consistent naming

* entity_ids => ent_ids

* Removing kb, cleaning up tests, making util functions private, use rsplit instead of split
This commit is contained in:
Kabir Khan 2019-06-16 04:29:04 -07:00 committed by Matthew Honnibal
parent 46c78d0a41
commit 1e19f34e29
3 changed files with 190 additions and 6 deletions
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106
.github/contributors/kabirkhan.md vendored Normal file
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@ -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 UG (haftungsbeschränkt)](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 | Kabir Khan |
| Company name (if applicable) | |
| Title or role (if applicable) | |
| Date | 2019-04-08 |
| GitHub username | kabirkhan |
| Website (optional) | |

64
spacy/pipeline/entityruler.py
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@ -48,6 +48,7 @@ class EntityRuler(object):
self.phrase_patterns = defaultdict(list)
self.matcher = Matcher(nlp.vocab)
self.phrase_matcher = PhraseMatcher(nlp.vocab)
self.ent_id_sep = cfg.get("ent_id_sep", "||")
patterns = cfg.get("patterns")
if patterns is not None:
self.add_patterns(patterns)
@ -84,7 +85,16 @@ class EntityRuler(object):
continue
# check for end - 1 here because boundaries are inclusive
if start not in seen_tokens and end - 1 not in seen_tokens:
new_entities.append(Span(doc, start, end, label=match_id))
if self.ent_ids:
label_ = self.nlp.vocab.strings[match_id]
ent_label, ent_id = self._split_label(label_)
span = Span(doc, start, end, label=ent_label)
if ent_id:
for token in span:
token.ent_id_ = ent_id
else:
span = Span(doc, start, end, label=match_id)
new_entities.append(span)
entities = [
e for e in entities if not (e.start < end and e.end > start)
]
@ -104,6 +114,21 @@ class EntityRuler(object):
all_labels.update(self.phrase_patterns.keys())
return tuple(all_labels)
@property
def ent_ids(self):
"""All entity ids present in the match patterns meta dicts.
RETURNS (set): The string entity ids.
DOCS: https://spacy.io/api/entityruler#labels
"""
all_ent_ids = set()
for l in self.labels:
if self.ent_id_sep in l:
_, ent_id = self._split_label(l)
all_ent_ids.add(ent_id)
return tuple(all_ent_ids)
@property
def patterns(self):
"""Get all patterns that were added to the entity ruler.
@ -115,10 +140,19 @@ class EntityRuler(object):
all_patterns = []
for label, patterns in self.token_patterns.items():
for pattern in patterns:
all_patterns.append({"label": label, "pattern": pattern})
ent_label, ent_id = self._split_label(label)
p = {"label": ent_label, "pattern": pattern}
if ent_id:
p["id"] = ent_id
all_patterns.append(p)
for label, patterns in self.phrase_patterns.items():
for pattern in patterns:
all_patterns.append({"label": label, "pattern": pattern.text})
ent_label, ent_id = self._split_label(label)
p = {"label": ent_label, "pattern": pattern.text}
if ent_id:
p["id"] = ent_id
all_patterns.append(p)
return all_patterns
def add_patterns(self, patterns):
@ -133,6 +167,8 @@ class EntityRuler(object):
"""
for entry in patterns:
label = entry["label"]
if "id" in entry:
label = self._create_label(label, entry["id"])
pattern = entry["pattern"]
if isinstance(pattern, basestring_):
self.phrase_patterns[label].append(self.nlp(pattern))
@ -145,6 +181,28 @@ class EntityRuler(object):
for label, patterns in self.phrase_patterns.items():
self.phrase_matcher.add(label, None, *patterns)
def _split_label(self, label):
"""Split Entity label into ent_label and ent_id if it contains self.ent_id_sep
RETURNS (tuple): ent_label, ent_id
"""
if self.ent_id_sep in label:
ent_label, ent_id = label.rsplit(self.ent_id_sep, 1)
else:
ent_label = label
ent_id = None
return ent_label, ent_id
def _create_label(self, label, ent_id):
"""Join Entity label with ent_id if the pattern has an `id` attribute
RETURNS (str): The ent_label joined with configured `ent_id_sep`
"""
if isinstance(ent_id, basestring_):
label = "{}{}{}".format(label, self.ent_id_sep, ent_id)
return label
def from_bytes(self, patterns_bytes, **kwargs):
"""Load the entity ruler from a bytestring.

26
spacy/tests/pipeline/test_entity_ruler.py
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@ -19,6 +19,7 @@ def patterns():
{"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
{"label": "HELLO", "pattern": [{"ORTH": "HELLO"}]},
{"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
{"label": "TECH_ORG", "pattern": "Apple", "id": "a1"},
]
@ -34,7 +35,7 @@ def add_ent():
def test_entity_ruler_init(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 3
assert len(ruler.labels) == 4
assert "HELLO" in ruler
assert "BYE" in ruler
nlp.add_pipe(ruler)
@ -77,14 +78,33 @@ def test_entity_ruler_existing_complex(nlp, patterns, add_ent):
assert len(doc.ents[1]) == 2
def test_entity_ruler_entity_id(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True)
nlp.add_pipe(ruler)
doc = nlp("Apple is a technology company")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "TECH_ORG"
assert doc.ents[0].ent_id_ == "a1"
def test_entity_ruler_cfg_ent_id_sep(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns, overwrite_ents=True, ent_id_sep="**")
assert "TECH_ORG**a1" in ruler.phrase_patterns
nlp.add_pipe(ruler)
doc = nlp("Apple is a technology company")
assert len(doc.ents) == 1
assert doc.ents[0].label_ == "TECH_ORG"
assert doc.ents[0].ent_id_ == "a1"
def test_entity_ruler_serialize_bytes(nlp, patterns):
ruler = EntityRuler(nlp, patterns=patterns)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 3
assert len(ruler.labels) == 4
ruler_bytes = ruler.to_bytes()
new_ruler = EntityRuler(nlp)
assert len(new_ruler) == 0
assert len(new_ruler.labels) == 0
new_ruler = new_ruler.from_bytes(ruler_bytes)
assert len(ruler) == len(patterns)
assert len(ruler.labels) == 3
assert len(ruler.labels) == 4