spaCy/website/api/phrasematcher.jade

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2017-10-03 15:27:22 +03:00
//- 💫 DOCS > API > PHRASEMATCHER
include ../_includes/_mixins
p
| The #[code PhraseMatcher] lets you efficiently match large terminology
| lists. While the #[+api("matcher") #[code Matcher]] lets you match
| squences based on lists of token descriptions, the #[code PhraseMatcher]
| accepts match patterns in the form of #[code Doc] objects.
+h(2, "init") PhraseMatcher.__init__
+tag method
p Create the rule-based #[code PhraseMatcher].
+aside-code("Example").
from spacy.matcher import PhraseMatcher
matcher = Matcher(nlp.vocab, max_length=6)
+table(["Name", "Type", "Description"])
+row
+cell #[code vocab]
+cell #[code Vocab]
+cell
| The vocabulary object, which must be shared with the documents
| the matcher will operate on.
+row
+cell #[code max_length]
+cell int
+cell Mamimum length of a phrase pattern to add.
+row("foot")
+cell returns
+cell #[code PhraseMatcher]
+cell The newly constructed object.
+h(2, "call") PhraseMatcher.__call__
+tag method
p Find all token sequences matching the supplied patterns on the #[code Doc].
+aside-code("Example").
from spacy.matcher import Matcher
matcher = Matcher(nlp.vocab)
matcher.add('OBAMA', None, nlp(u"Barack Obama"))
doc = nlp(u"Barack Obama lifts America one last time in emotional farewell")
matches = matcher(doc)
+table(["Name", "Type", "Description"])
+row
+cell #[code doc]
+cell #[code Doc]
+cell The document to match over.
+row("foot")
+cell returns
+cell list
+cell
| A list of #[code (match_id, start, end)] tuples, describing the
| matches. A match tuple describes a span #[code doc[start:end]].
| The #[code match_id] is the ID of the added match pattern.
+h(2, "pipe") PhraseMatcher.pipe
+tag method
p Match a stream of documents, yielding them in turn.
+aside-code("Example").
from spacy.matcher import PhraseMatcher
matcher = PhraseMatcher(nlp.vocab)
for doc in matcher.pipe(texts, batch_size=50, n_threads=4):
pass
+table(["Name", "Type", "Description"])
+row
+cell #[code docs]
+cell iterable
+cell A stream of documents.
+row
+cell #[code batch_size]
+cell int
+cell The number of documents to accumulate into a working set.
+row
+cell #[code n_threads]
+cell int
+cell
| The number of threads with which to work on the buffer in
| parallel, if the #[code PhraseMatcher] implementation supports
| multi-threading.
+row("foot")
+cell yields
+cell #[code Doc]
+cell Documents, in order.
+h(2, "len") PhraseMatcher.__len__
+tag method
p
| Get the number of rules added to the matcher. Note that this only returns
| the number of rules (identical with the number of IDs), not the number
| of individual patterns.
+aside-code("Example").
matcher = PhraseMatcher(nlp.vocab)
assert len(matcher) == 0
matcher.add('OBAMA', None, nlp(u"Barack Obama"))
assert len(matcher) == 1
+table(["Name", "Type", "Description"])
+row("foot")
+cell returns
+cell int
+cell The number of rules.
+h(2, "contains") PhraseMatcher.__contains__
+tag method
p Check whether the matcher contains rules for a match ID.
+aside-code("Example").
matcher = PhraseMatcher(nlp.vocab)
assert len(matcher) == 0
matcher.add('OBAMA', None, nlp(u"Barack Obama"))
assert len(matcher) == 1
+table(["Name", "Type", "Description"])
+row
+cell #[code key]
+cell unicode
+cell The match ID.
+row("foot")
+cell returns
+cell int
+cell Whether the matcher contains rules for this match ID.
+h(2, "add") PhraseMatcher.add
+tag method
p
| Add a rule to the matcher, consisting of an ID key, one or more patterns, and
| a callback function to act on the matches. The callback function will
| receive the arguments #[code matcher], #[code doc], #[code i] and
| #[code matches]. If a pattern already exists for the given ID, the
| patterns will be extended. An #[code on_match] callback will be
| overwritten.
+aside-code("Example").
def on_match(matcher, doc, id, matches):
print('Matched!', matches)
matcher = PhraseMatcher(nlp.vocab)
matcher.add('OBAMA', on_match, nlp(u"Barack Obama"))
matcher.add('HEALTH', on_match, nlp(u"health care reform"),
nlp(u"healthcare reform"))
doc = nlp(u"Barack Obama urges Congress to find courage to defend his healthcare reforms")
matches = matcher(doc)
+table(["Name", "Type", "Description"])
+row
+cell #[code match_id]
+cell unicode
+cell An ID for the thing you're matching.
+row
+cell #[code on_match]
+cell callable or #[code None]
+cell
| Callback function to act on matches. Takes the arguments
| #[code matcher], #[code doc], #[code i] and #[code matches].
+row
+cell #[code *docs]
+cell list
+cell
| #[code Doc] objects of the phrases to match.