spaCy/spacy/matcher.pyx

307 lines
10 KiB
Cython

# cython: profile=True
from __future__ import unicode_literals
from os import path
from .typedefs cimport attr_t
from .typedefs cimport hash_t
from .attrs cimport attr_id_t
from .structs cimport TokenC, LexemeC
from .lexeme cimport Lexeme
from cymem.cymem cimport Pool
from preshed.maps cimport PreshMap
from libcpp.vector cimport vector
from murmurhash.mrmr cimport hash64
from .attrs cimport LENGTH, ENT_TYPE, ORTH, NORM, LEMMA, LOWER, SHAPE
from .attrs cimport FLAG14, FLAG15, FLAG16, FLAG17, FLAG18, FLAG19, FLAG20, FLAG21, FLAG22, FLAG23, FLAG24, FLAG25
from .tokens.doc cimport get_token_attr
from .tokens.doc cimport Doc
from .vocab cimport Vocab
from libcpp.vector cimport vector
from .attrs import FLAG61 as U_ENT
from .attrs import FLAG60 as B2_ENT
from .attrs import FLAG59 as B3_ENT
from .attrs import FLAG58 as B4_ENT
from .attrs import FLAG57 as B5_ENT
from .attrs import FLAG56 as B6_ENT
from .attrs import FLAG55 as B7_ENT
from .attrs import FLAG54 as B8_ENT
from .attrs import FLAG53 as B9_ENT
from .attrs import FLAG52 as B10_ENT
from .attrs import FLAG51 as I3_ENT
from .attrs import FLAG50 as I4_ENT
from .attrs import FLAG49 as I5_ENT
from .attrs import FLAG48 as I6_ENT
from .attrs import FLAG47 as I7_ENT
from .attrs import FLAG46 as I8_ENT
from .attrs import FLAG45 as I9_ENT
from .attrs import FLAG44 as I10_ENT
from .attrs import FLAG43 as L2_ENT
from .attrs import FLAG42 as L3_ENT
from .attrs import FLAG41 as L4_ENT
from .attrs import FLAG40 as L5_ENT
from .attrs import FLAG39 as L6_ENT
from .attrs import FLAG38 as L7_ENT
from .attrs import FLAG37 as L8_ENT
from .attrs import FLAG36 as L9_ENT
from .attrs import FLAG35 as L10_ENT
try:
import ujson as json
except ImportError:
import json
cdef struct AttrValue:
attr_id_t attr
attr_t value
cdef struct Pattern:
AttrValue* spec
int length
cdef Pattern* init_pattern(Pool mem, object token_specs, attr_t entity_type) except NULL:
pattern = <Pattern*>mem.alloc(len(token_specs) + 1, sizeof(Pattern))
cdef int i
for i, spec in enumerate(token_specs):
pattern[i].spec = <AttrValue*>mem.alloc(len(spec), sizeof(AttrValue))
pattern[i].length = len(spec)
for j, (attr, value) in enumerate(spec):
pattern[i].spec[j].attr = attr
pattern[i].spec[j].value = value
i = len(token_specs)
pattern[i].spec = <AttrValue*>mem.alloc(2, sizeof(AttrValue))
pattern[i].spec[0].attr = ENT_TYPE
pattern[i].spec[0].value = entity_type
pattern[i].spec[1].attr = LENGTH
pattern[i].spec[1].value = len(token_specs)
pattern[i].length = 0
return pattern
cdef int match(const Pattern* pattern, const TokenC* token) except -1:
cdef int i
for i in range(pattern.length):
if get_token_attr(token, pattern.spec[i].attr) != pattern.spec[i].value:
return False
return True
cdef int is_final(const Pattern* pattern) except -1:
return (pattern + 1).length == 0
cdef object get_entity(const Pattern* pattern, const TokenC* tokens, int i):
pattern += 1
i += 1
return (pattern.spec[0].value, i - pattern.spec[1].value, i)
def _convert_strings(token_specs, string_store):
converted = []
for spec in token_specs:
converted.append([])
for attr, value in spec.items():
if isinstance(attr, basestring):
attr = map_attr_name(attr)
if isinstance(value, basestring):
value = string_store[value]
if isinstance(value, bool):
value = int(value)
converted[-1].append((attr, value))
return converted
def get_bilou(length):
if length == 1:
return [U_ENT]
elif length == 2:
return [B2_ENT, L2_ENT]
elif length == 3:
return [B3_ENT, I3_ENT, L3_ENT]
elif length == 4:
return [B4_ENT, I4_ENT, I4_ENT, L4_ENT]
elif length == 5:
return [B5_ENT, I5_ENT, I5_ENT, I5_ENT, L5_ENT]
elif length == 6:
return [B6_ENT, I6_ENT, I6_ENT, I6_ENT, I6_ENT, L6_ENT]
elif length == 7:
return [B7_ENT, I7_ENT, I7_ENT, I7_ENT, I7_ENT, I7_ENT, L7_ENT]
elif length == 8:
return [B8_ENT, I8_ENT, I8_ENT, I8_ENT, I8_ENT, I8_ENT, I8_ENT, L8_ENT]
elif length == 9:
return [B9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, L9_ENT]
elif length == 10:
return [B10_ENT, I10_ENT, I10_ENT, I10_ENT, I10_ENT, I10_ENT, I10_ENT,
I10_ENT, I10_ENT, L10_ENT]
else:
raise ValueError("Max length currently 10 for phrase matching")
def map_attr_name(attr):
attr = attr.upper()
if attr == 'ORTH':
return ORTH
elif attr == 'LEMMA':
return LEMMA
elif attr == 'LOWER':
return LOWER
elif attr == 'SHAPE':
return SHAPE
elif attr == 'NORM':
return NORM
else:
raise Exception("TODO: Finish supporting attr mapping %s" % attr)
cdef class Matcher:
cdef Pool mem
cdef vector[Pattern*] patterns
cdef readonly Vocab vocab
def __init__(self, vocab, patterns):
self.vocab = vocab
self.mem = Pool()
self.vocab = vocab
for entity_key, (etype, attrs, specs) in sorted(patterns.items()):
self.add(entity_key, etype, attrs, specs)
@classmethod
def from_dir(cls, data_dir, Vocab vocab):
patterns_loc = path.join(data_dir, 'vocab', 'gazetteer.json')
if path.exists(patterns_loc):
patterns_data = open(patterns_loc).read()
patterns = json.loads(patterns_data)
return cls(vocab, patterns)
else:
return cls(vocab, {})
property n_patterns:
def __get__(self): return self.patterns.size()
def add(self, entity_key, etype, attrs, specs):
if isinstance(entity_key, basestring):
entity_key = self.vocab.strings[entity_key]
if isinstance(etype, basestring):
etype = self.vocab.strings[etype]
elif etype is None:
etype = -1
# TODO: Do something more clever about multiple patterns for single
# entity
for spec in specs:
spec = _convert_strings(spec, self.vocab.strings)
self.patterns.push_back(init_pattern(self.mem, spec, etype))
def __call__(self, Doc doc, acceptor=None):
cdef vector[Pattern*] partials
cdef int n_partials = 0
cdef int q = 0
cdef int i, token_i
cdef const TokenC* token
cdef Pattern* state
matches = []
for token_i in range(doc.length):
token = &doc.data[token_i]
q = 0
# Go over the open matches, extending or finalizing if able. Otherwise,
# we over-write them (q doesn't advance)
for i in range(partials.size()):
state = partials.at(i)
if match(state, token):
if is_final(state):
label, start, end = get_entity(state, token, token_i)
if acceptor is None or acceptor(doc, label, start, end):
matches.append((label, start, end))
else:
partials[q] = state + 1
q += 1
partials.resize(q)
# Check whether we open any new patterns on this token
for i in range(self.n_patterns):
state = self.patterns[i]
if match(state, token):
if is_final(state):
label, start, end = get_entity(state, token, token_i)
if acceptor is None or acceptor(doc, label, start, end):
matches.append((label, start, end))
else:
partials.push_back(state + 1)
doc.ents = [(e.label, e.start, e.end) for e in doc.ents] + matches
return matches
cdef class PhraseMatcher:
cdef Pool mem
cdef Vocab vocab
cdef Matcher matcher
cdef PreshMap phrase_ids
cdef int max_length
cdef attr_t* _phrase_key
def __init__(self, Vocab vocab, phrases, max_length=10):
self.mem = Pool()
self._phrase_key = <attr_t*>self.mem.alloc(max_length, sizeof(attr_t))
self.max_length = max_length
self.vocab = vocab
self.matcher = Matcher(self.vocab, {})
self.phrase_ids = PreshMap()
for phrase in phrases:
if len(phrase) < max_length:
self.add(phrase)
abstract_patterns = []
for length in range(1, max_length):
abstract_patterns.append([{tag: True} for tag in get_bilou(length)])
self.matcher.add('Candidate', 'MWE', {}, abstract_patterns)
def add(self, Doc tokens):
cdef int length = tokens.length
assert length < self.max_length
tags = get_bilou(length)
assert len(tags) == length, length
cdef int i
for i in range(self.max_length):
self._phrase_key[i] = 0
for i, tag in enumerate(tags):
lexeme = self.vocab[tokens.data[i].lex.orth]
lexeme.set_flag(tag, True)
self._phrase_key[i] = lexeme.orth
cdef hash_t key = hash64(self._phrase_key, self.max_length * sizeof(attr_t), 0)
self.phrase_ids[key] = True
def __call__(self, Doc doc):
matches = []
for label, start, end in self.matcher(doc, acceptor=self.accept_match):
cand = doc[start : end]
start = cand[0].idx
end = cand[-1].idx + len(cand[-1])
matches.append((start, end, cand.root.tag_, cand.text, 'MWE'))
for match in matches:
doc.merge(*match)
return matches
def accept_match(self, Doc doc, int label, int start, int end):
assert (end - start) < self.max_length
cdef int i, j
for i in range(self.max_length):
self._phrase_key[i] = 0
for i, j in enumerate(range(start, end)):
self._phrase_key[i] = doc.data[j].lex.orth
cdef hash_t key = hash64(self._phrase_key, self.max_length * sizeof(attr_t), 0)
if self.phrase_ids.get(key):
return True
else:
return False