diff --git a/spacy/matcher.pyx b/spacy/matcher.pyx index 64fd4e683..017ac5973 100644 --- a/spacy/matcher.pyx +++ b/spacy/matcher.pyx @@ -12,9 +12,11 @@ from .lexeme cimport Lexeme from cymem.cymem cimport Pool from preshed.maps cimport PreshMap from libcpp.vector cimport vector +from libcpp.pair cimport pair from murmurhash.mrmr cimport hash64 +from libc.stdint cimport int32_t -from .attrs cimport LENGTH, ENT_TYPE, ORTH, NORM, LEMMA, LOWER, SHAPE +from .attrs cimport ID, LENGTH, ENT_TYPE, ORTH, NORM, LEMMA, LOWER, SHAPE from . import attrs from .tokens.doc cimport get_token_attr from .tokens.doc cimport Doc @@ -59,58 +61,96 @@ except ImportError: import json -cdef struct AttrValue: +cpdef enum quantifier_t: + _META + ONE + ZERO + ZERO_ONE + ZERO_PLUS + + +cdef enum action_t: + REJECT + ADVANCE + REPEAT + ACCEPT + ADVANCE_ZERO + PANIC + + +cdef struct AttrValueC: attr_id_t attr attr_t value -cdef struct Pattern: - AttrValue* spec - int length +cdef struct TokenPatternC: + AttrValueC* attrs + int32_t nr_attr + quantifier_t quantifier -cdef Pattern* init_pattern(Pool mem, object token_specs, attr_t entity_type) except NULL: - pattern = mem.alloc(len(token_specs) + 1, sizeof(Pattern)) +ctypedef TokenPatternC* TokenPatternC_ptr +ctypedef pair[int, TokenPatternC_ptr] StateC + + +cdef TokenPatternC* init_pattern(Pool mem, object token_specs, attr_t entity_id, + attr_t entity_type) except NULL: + pattern = mem.alloc(len(token_specs) + 1, sizeof(TokenPatternC)) cdef int i - for i, spec in enumerate(token_specs): - pattern[i].spec = mem.alloc(len(spec), sizeof(AttrValue)) - pattern[i].length = len(spec) + for i, (quantifier, spec) in enumerate(token_specs): + pattern[i].quantifier = quantifier + pattern[i].attrs = mem.alloc(len(spec), sizeof(AttrValueC)) + pattern[i].nr_attr = len(spec) for j, (attr, value) in enumerate(spec): - pattern[i].spec[j].attr = attr - pattern[i].spec[j].value = value + pattern[i].attrs[j].attr = attr + pattern[i].attrs[j].value = value i = len(token_specs) - pattern[i].spec = 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 + pattern[i].attrs = mem.alloc(3, sizeof(AttrValueC)) + pattern[i].attrs[0].attr = ID + pattern[i].attrs[0].value = entity_id + pattern[i].attrs[1].attr = ENT_TYPE + pattern[i].attrs[1].value = entity_type + pattern[i].nr_attr = 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) +cdef int get_action(const TokenPatternC* pattern, const TokenC* token) nogil: + for attr in pattern.attrs[:pattern.nr_attr]: + if get_token_attr(token, attr.attr) != attr.value: + if pattern.quantifier == ONE: + return REJECT + elif pattern.quantifier == ZERO: + return ACCEPT if (pattern+1).nr_attr == 0 else ADVANCE + elif pattern.quantifier in (ZERO_ONE, ZERO_PLUS): + return ACCEPT if (pattern+1).nr_attr == 0 else ADVANCE_ZERO + else: + return PANIC + if pattern.quantifier == ZERO: + return REJECT + elif pattern.quantifier in (ONE, ZERO_ONE): + return ACCEPT if (pattern+1).nr_attr == 0 else ADVANCE + elif pattern.quantifier == ZERO_PLUS: + return REPEAT + else: + return PANIC def _convert_strings(token_specs, string_store): - converted = [] + # Support 'syntactic sugar' operator '+', as combination of ONE, ZERO_PLUS + operators = {'!': (ZERO,), '*': (ZERO_PLUS,), '+': (ONE, ZERO_PLUS), + '?': (ZERO_ONE,)} + tokens = [] + op = ONE for spec in token_specs: - converted.append([]) + token = [] + ops = (ONE,) for attr, value in spec.items(): + if isinstance(attr, basestring) and attr.upper() == 'OP': + if value in operators: + ops = operators[value] + else: + raise KeyError( + "Unknown operator. Options: %s" % ', '.join(operators.keys())) if isinstance(attr, basestring): attr = attrs.IDS.get(attr.upper()) if isinstance(value, basestring): @@ -118,8 +158,10 @@ def _convert_strings(token_specs, string_store): if isinstance(value, bool): value = int(value) if attr is not None: - converted[-1].append((attr, value)) - return converted + token.append((attr, value)) + for op in ops: + tokens.append((op, token)) + return tokens def get_bilou(length): @@ -150,7 +192,7 @@ def get_bilou(length): cdef class Matcher: cdef Pool mem - cdef vector[Pattern*] patterns + cdef vector[TokenPatternC*] patterns cdef readonly Vocab vocab cdef object _patterns @@ -189,15 +231,15 @@ cdef class Matcher: # entity for spec in specs: spec = _convert_strings(spec, self.vocab.strings) - self.patterns.push_back(init_pattern(self.mem, spec, etype)) + self.patterns.push_back(init_pattern(self.mem, spec, entity_key, etype)) def __call__(self, Doc doc, acceptor=None): - cdef vector[Pattern*] partials + cdef vector[StateC] partials cdef int n_partials = 0 cdef int q = 0 cdef int i, token_i cdef const TokenC* token - cdef Pattern* state + cdef StateC state matches = [] for token_i in range(doc.length): token = &doc.c[token_i] @@ -205,27 +247,57 @@ cdef class Matcher: # Go over the open matches, extending or finalizing if able. Otherwise, # we over-write them (q doesn't advance) for state in partials: - 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 + action = get_action(state.second, token) + while action == ADVANCE_ZERO: + state.second += 1 + action = get_action(state.second, token) + if action == REPEAT: + # Leave the state in the queue, and advance to next slot + # (i.e. we don't overwrite -- we want to greedily match more + # pattern. + q += 1 + elif action == REJECT: + pass + elif action == ADVANCE: + partials[q].second += 1 + q += 1 + elif action == ACCEPT: + # TODO: What to do about patterns starting with ZERO? Need to + # adjust the start position. + start = state.first + end = token_i+1 + ent_id = state.second[1].attrs[0].value + label = state.second[1].attrs[1].value + if acceptor is None or acceptor(doc, ent_id, label, start, end): + matches.append((ent_id, label, start, end)) partials.resize(q) # Check whether we open any new patterns on this token - for state in self.patterns: - 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) + for pattern in self.patterns: + action = get_action(pattern, token) + while action == ADVANCE_ZERO: + pattern += 1 + action = get_action(pattern, token) + if action == REPEAT: + state.first = token_i + state.second = pattern + partials.push_back(state) + elif action == ADVANCE: + # TODO: What to do about patterns starting with ZERO? Need to + # adjust the start position. + state.first = token_i + state.second = pattern + 1 + partials.push_back(state) + elif action == ACCEPT: + start = token_i + end = token_i+1 + ent_id = pattern[1].attrs[0].value + label = pattern[1].attrs[1].value + if acceptor is None or acceptor(doc, ent_id, label, start, end): + matches.append((ent_id, label, start, end)) seen = set() filtered = [] - for label, start, end in sorted(matches, key=lambda m: (m[1], -(m[1] - m[2]))): + for ent_id, label, start, end in sorted(matches, + key=lambda m: (m[2],-(m[2]-m[3]))): if all(i in seen for i in range(start, end)): continue else: diff --git a/spacy/structs.pxd b/spacy/structs.pxd index f7e6b1ec7..ae1cfb434 100644 --- a/spacy/structs.pxd +++ b/spacy/structs.pxd @@ -29,6 +29,7 @@ cdef struct LexemeC: cdef struct Entity: + hash_t id int start int end int label @@ -53,4 +54,5 @@ cdef struct TokenC: uint32_t r_edge int ent_iob - int ent_type + int ent_type # TODO: Is there a better way to do this? Multiple sources of truth.. + hash_t ent_id diff --git a/spacy/tests/test_matcher.py b/spacy/tests/test_matcher.py index 986d8a8bd..9dce3177f 100644 --- a/spacy/tests/test_matcher.py +++ b/spacy/tests/test_matcher.py @@ -6,46 +6,85 @@ from spacy.matcher import * from spacy.attrs import LOWER from spacy.tokens.doc import Doc from spacy.vocab import Vocab +from spacy.en import English @pytest.fixture -def matcher(EN): +def matcher(): patterns = { - 'Javascript': ['PRODUCT', {}, [[{'ORTH': 'JavaScript'}]]], + 'JS': ['PRODUCT', {}, [[{'ORTH': 'JavaScript'}]]], 'GoogleNow': ['PRODUCT', {}, [[{'ORTH': 'Google'}, {'ORTH': 'Now'}]]], 'Java': ['PRODUCT', {}, [[{'LOWER': 'java'}]]], } - return Matcher(EN.vocab, patterns) + return Matcher(Vocab(get_lex_attr=English.default_lex_attrs()), patterns) def test_compile(matcher): assert matcher.n_patterns == 3 -def test_no_match(matcher, EN): - tokens = EN('I like cheese') - assert matcher(tokens) == [] +def test_no_match(matcher): + doc = Doc(matcher.vocab, ['I', 'like', 'cheese', '.']) + assert matcher(doc) == [] -def test_match_start(matcher, EN): - tokens = EN('JavaScript is good') - assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 0, 1)] +def test_match_start(matcher): + doc = Doc(matcher.vocab, ['JavaScript', 'is', 'good']) + assert matcher(doc) == [(matcher.vocab.strings['JS'], + matcher.vocab.strings['PRODUCT'], 0, 1)] -def test_match_end(matcher, EN): - tokens = EN('I like java') - assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 2, 3)] +def test_match_end(matcher): + doc = Doc(matcher.vocab, ['I', 'like', 'java']) + assert matcher(doc) == [(doc.vocab.strings['Java'], + doc.vocab.strings['PRODUCT'], 2, 3)] -def test_match_middle(matcher, EN): - tokens = EN('I like Google Now best') - assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 2, 4)] +def test_match_middle(matcher): + doc = Doc(matcher.vocab, ['I', 'like', 'Google', 'Now', 'best']) + assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], + doc.vocab.strings['PRODUCT'], 2, 4)] -def test_match_multi(matcher, EN): - tokens = EN('I like Google Now and java best') - assert matcher(tokens) == [(EN.vocab.strings['PRODUCT'], 2, 4), - (EN.vocab.strings['PRODUCT'], 5, 6)] +def test_match_multi(matcher): + doc = Doc(matcher.vocab, 'I like Google Now and java best'.split()) + assert matcher(doc) == [(doc.vocab.strings['GoogleNow'], + doc.vocab.strings['PRODUCT'], 2, 4), + (doc.vocab.strings['Java'], + doc.vocab.strings['PRODUCT'], 5, 6)] + +def test_match_zero(matcher): + matcher.add('Quote', '', {}, [ + [ + {'ORTH': '"'}, + {'OP': '!', 'IS_PUNCT': True}, + {'OP': '!', 'IS_PUNCT': True}, + {'ORTH': '"'} + ]]) + doc = Doc(matcher.vocab, 'He said , " some words " ...'.split()) + assert len(matcher(doc)) == 1 + doc = Doc(matcher.vocab, 'He said , " some three words " ...'.split()) + assert len(matcher(doc)) == 0 + matcher.add('Quote', '', {}, [ + [ + {'ORTH': '"'}, + {'IS_PUNCT': True}, + {'IS_PUNCT': True}, + {'IS_PUNCT': True}, + {'ORTH': '"'} + ]]) + assert len(matcher(doc)) == 0 + + +def test_match_zero_plus(matcher): + matcher.add('Quote', '', {}, [ + [ + {'ORTH': '"'}, + {'OP': '*', 'IS_PUNCT': False}, + {'ORTH': '"'} + ]]) + doc = Doc(matcher.vocab, 'He said , " some words " ...'.split()) + assert len(matcher(doc)) == 1 @pytest.mark.models diff --git a/spacy/tokens/span.pyx b/spacy/tokens/span.pyx index 884bb74d8..159074cd4 100644 --- a/spacy/tokens/span.pyx +++ b/spacy/tokens/span.pyx @@ -241,6 +241,27 @@ cdef class Span: for word in self.rights: yield from word.subtree + property ent_id: + '''An (integer) entity ID. Usually assigned by patterns in the Matcher.''' + def __get__(self): + return self.root.ent_id + + def __set__(self, hash_t key): + # TODO + raise NotImplementedError( + "Can't yet set ent_id from Span. Vote for this feature on the issue " + "tracker: http://github.com/spacy-io/spaCy") + property ent_id_: + '''A (string) entity ID. Usually assigned by patterns in the Matcher.''' + def __get__(self): + return self.root.ent_id_ + + def __set__(self, hash_t key): + # TODO + raise NotImplementedError( + "Can't yet set ent_id_ from Span. Vote for this feature on the issue " + "tracker: http://github.com/spacy-io/spaCy") + property orth_: def __get__(self): return ''.join([t.string for t in self]).strip() diff --git a/spacy/tokens/token.pxd b/spacy/tokens/token.pxd index 1706cdc55..aa2f09394 100644 --- a/spacy/tokens/token.pxd +++ b/spacy/tokens/token.pxd @@ -5,10 +5,9 @@ from .doc cimport Doc cdef class Token: - cdef Vocab vocab + cdef readonly Vocab vocab cdef TokenC* c cdef readonly int i - cdef int array_len cdef readonly Doc doc @staticmethod diff --git a/spacy/tokens/token.pyx b/spacy/tokens/token.pyx index 0221a1eb9..9f1a70636 100644 --- a/spacy/tokens/token.pyx +++ b/spacy/tokens/token.pyx @@ -58,7 +58,6 @@ cdef class Token: self.doc = doc self.c = &self.doc.c[offset] self.i = offset - self.array_len = doc.length def __len__(self): return self.c.lex.length @@ -410,6 +409,28 @@ cdef class Token: iob_strings = ('', 'I', 'O', 'B') return iob_strings[self.c.ent_iob] + property ent_id: + '''An (integer) entity ID. Usually assigned by patterns in the Matcher.''' + def __get__(self): + return self.c.ent.ent_id + + def __set__(self, hash_t key): + # TODO + raise NotImplementedError( + "Can't yet set ent_id from Token. Vote for this feature on the issue " + "tracker: http://github.com/spacy-io/spaCy") + + property ent_id_: + '''A (string) entity ID. Usually assigned by patterns in the Matcher.''' + def __get__(self): + return self.vocab.strings[self.c.ent_id] + + def __set__(self, hash_t key): + # TODO + raise NotImplementedError( + "Can't yet set ent_id_ from Token. Vote for this feature on the issue " + "tracker: http://github.com/spacy-io/spaCy") + property whitespace_: def __get__(self): return ' ' if self.c.spacy else '' @@ -507,3 +528,17 @@ cdef class Token: property like_email: def __get__(self): return Lexeme.c_check_flag(self.c.lex, LIKE_EMAIL) + + + + + +doc = nlp('Google Now is a moribund project destined for closure.') + +google_now = doc.ents[0] # Span instance + +google_now.attrs['category'] == 'TECHNOLOGY' + +ent_id = google_now.ent_id + +attrs = nlp.matcher.get_attrs(ent_id)