mirror of
https://github.com/explosion/spaCy.git
synced 2025-10-30 23:47:31 +03:00
This reverts commit 58bdd8607b.
This commit is contained in:
Adriane Boyd
GitHub
parent
6a8619dd73
commit
add52935ff
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@ -108,8 +108,8 @@ apple =
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thinc-apple-ops>=0.0.4,<1.0.0
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# Language tokenizers with external dependencies
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ja =
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sudachipy>=0.5.2,!=0.6.1
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sudachidict_core>=20211220
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sudachipy>=0.4.9
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sudachidict_core>=20200330
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ko =
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natto-py==0.9.0
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th =
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@ -45,10 +45,6 @@ _hangul_syllables = r"\uAC00-\uD7AF"
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_hangul_jamo = r"\u1100-\u11FF"
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_hangul = _hangul_syllables + _hangul_jamo
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_hiragana = r"\u3040-\u309F"
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_katakana = r"\u30A0-\u30FFー"
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_kana = _hiragana + _katakana
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# letters with diacritics - Catalan, Czech, Latin, Latvian, Lithuanian, Polish, Slovak, Turkish, Welsh
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_latin_u_extendedA = (
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r"\u0100\u0102\u0104\u0106\u0108\u010A\u010C\u010E\u0110\u0112\u0114\u0116\u0118\u011A\u011C"
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@ -248,7 +244,6 @@ _uncased = (
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+ _tamil
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+ _telugu
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+ _hangul
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+ _kana
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+ _cjk
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)
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@ -6,35 +6,16 @@ from ...tokens import Doc, Span
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def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
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"""
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Detect base noun phrases from a dependency parse. Works on both Doc and Span.
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"""
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labels = [
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"nsubj",
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"nsubj:pass",
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"obj",
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"obl",
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"obl:agent",
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"obl:arg",
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"obl:mod",
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"nmod",
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"pcomp",
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"appos",
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"ROOT",
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]
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post_modifiers = ["flat", "flat:name", "flat:foreign", "fixed", "compound"]
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"""Detect base noun phrases from a dependency parse. Works on Doc and Span."""
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# fmt: off
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labels = ["nsubj", "nsubj:pass", "obj", "iobj", "ROOT", "appos", "nmod", "nmod:poss"]
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# fmt: on
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doc = doclike.doc # Ensure works on both Doc and Span.
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if not doc.has_annotation("DEP"):
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raise ValueError(Errors.E029)
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np_deps = {doc.vocab.strings.add(label) for label in labels}
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np_modifs = {doc.vocab.strings.add(modifier) for modifier in post_modifiers}
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np_deps = [doc.vocab.strings[label] for label in labels]
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conj = doc.vocab.strings.add("conj")
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np_label = doc.vocab.strings.add("NP")
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adj_label = doc.vocab.strings.add("amod")
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det_label = doc.vocab.strings.add("det")
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det_pos = doc.vocab.strings.add("DET")
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adp_pos = doc.vocab.strings.add("ADP")
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conj_label = doc.vocab.strings.add("conj")
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conj_pos = doc.vocab.strings.add("CCONJ")
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prev_end = -1
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for i, word in enumerate(doclike):
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if word.pos not in (NOUN, PROPN, PRON):
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@ -43,45 +24,16 @@ def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
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if word.left_edge.i <= prev_end:
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continue
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if word.dep in np_deps:
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right_childs = list(word.rights)
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right_child = right_childs[0] if right_childs else None
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if right_child:
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if (
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right_child.dep == adj_label
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): # allow chain of adjectives by expanding to right
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right_end = right_child.right_edge
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elif (
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right_child.dep == det_label and right_child.pos == det_pos
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): # cut relative pronouns here
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right_end = right_child
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elif right_child.dep in np_modifs: # Check if we can expand to right
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right_end = word.right_edge
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else:
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right_end = word
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else:
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right_end = word
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prev_end = right_end.i
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left_index = word.left_edge.i
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left_index = (
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left_index + 1 if word.left_edge.pos == adp_pos else left_index
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)
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yield left_index, right_end.i + 1, np_label
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elif word.dep == conj_label:
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prev_end = word.right_edge.i
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yield word.left_edge.i, word.right_edge.i + 1, np_label
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elif word.dep == conj:
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head = word.head
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while head.dep == conj_label and head.head.i < head.i:
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while head.dep == conj and head.head.i < head.i:
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head = head.head
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# If the head is an NP, and we're coordinated to it, we're an NP
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if head.dep in np_deps:
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prev_end = word.i
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left_index = word.left_edge.i # eliminate left attached conjunction
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left_index = (
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left_index + 1 if word.left_edge.pos == conj_pos else left_index
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)
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yield left_index, word.i + 1, np_label
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prev_end = word.right_edge.i
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yield word.left_edge.i, word.right_edge.i + 1, np_label
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SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
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@ -6,15 +6,13 @@ from .tokenizer_exceptions import TOKENIZER_EXCEPTIONS
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from .punctuation import TOKENIZER_PREFIXES, TOKENIZER_INFIXES
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from ...language import Language, BaseDefaults
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from .lemmatizer import ItalianLemmatizer
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from .syntax_iterators import SYNTAX_ITERATORS
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class ItalianDefaults(BaseDefaults):
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tokenizer_exceptions = TOKENIZER_EXCEPTIONS
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stop_words = STOP_WORDS
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prefixes = TOKENIZER_PREFIXES
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infixes = TOKENIZER_INFIXES
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stop_words = STOP_WORDS
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syntax_iterators = SYNTAX_ITERATORS
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class Italian(Language):
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@ -1,86 +0,0 @@
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from typing import Union, Iterator, Tuple
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from ...symbols import NOUN, PROPN, PRON
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from ...errors import Errors
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from ...tokens import Doc, Span
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def noun_chunks(doclike: Union[Doc, Span]) -> Iterator[Tuple[int, int, int]]:
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"""
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Detect base noun phrases from a dependency parse. Works on both Doc and Span.
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"""
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labels = [
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"nsubj",
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"nsubj:pass",
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"obj",
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"obl",
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"obl:agent",
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"nmod",
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"pcomp",
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"appos",
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"ROOT",
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]
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post_modifiers = ["flat", "flat:name", "fixed", "compound"]
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dets = ["det", "det:poss"]
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doc = doclike.doc # Ensure works on both Doc and Span.
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if not doc.has_annotation("DEP"):
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raise ValueError(Errors.E029)
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np_deps = {doc.vocab.strings.add(label) for label in labels}
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np_modifs = {doc.vocab.strings.add(modifier) for modifier in post_modifiers}
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np_label = doc.vocab.strings.add("NP")
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adj_label = doc.vocab.strings.add("amod")
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det_labels = {doc.vocab.strings.add(det) for det in dets}
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det_pos = doc.vocab.strings.add("DET")
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adp_label = doc.vocab.strings.add("ADP")
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conj = doc.vocab.strings.add("conj")
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conj_pos = doc.vocab.strings.add("CCONJ")
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prev_end = -1
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for i, word in enumerate(doclike):
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if word.pos not in (NOUN, PROPN, PRON):
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continue
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# Prevent nested chunks from being produced
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if word.left_edge.i <= prev_end:
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continue
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if word.dep in np_deps:
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right_childs = list(word.rights)
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right_child = right_childs[0] if right_childs else None
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if right_child:
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if (
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right_child.dep == adj_label
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): # allow chain of adjectives by expanding to right
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right_end = right_child.right_edge
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elif (
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right_child.dep in det_labels and right_child.pos == det_pos
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): # cut relative pronouns here
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right_end = right_child
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elif right_child.dep in np_modifs: # Check if we can expand to right
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right_end = word.right_edge
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else:
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right_end = word
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else:
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right_end = word
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prev_end = right_end.i
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left_index = word.left_edge.i
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left_index = (
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left_index + 1 if word.left_edge.pos == adp_label else left_index
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)
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yield left_index, right_end.i + 1, np_label
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elif word.dep == conj:
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head = word.head
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while head.dep == conj and head.head.i < head.i:
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head = head.head
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# If the head is an NP, and we're coordinated to it, we're an NP
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if head.dep in np_deps:
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prev_end = word.i
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left_index = word.left_edge.i # eliminate left attached conjunction
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left_index = (
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left_index + 1 if word.left_edge.pos == conj_pos else left_index
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)
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yield left_index, word.i + 1, np_label
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SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
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@ -4,42 +4,46 @@ alle allerede alt and andre annen annet at av
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bak bare bedre beste blant ble bli blir blitt bris by både
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da dag de del dem den denne der dermed det dette disse du
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da dag de del dem den denne der dermed det dette disse drept du
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eller en enn er et ett etter
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fem fikk fire fjor flere folk for fortsatt fra fram
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fem fikk fire fjor flere folk for fortsatt fotball fra fram frankrike fredag
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funnet få får fått før først første
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gang gi gikk gjennom gjorde gjort gjør gjøre god godt grunn gå går
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ha hadde ham han hans har hele helt henne hennes her hun
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ha hadde ham han hans har hele helt henne hennes her hun hva hvor hvordan
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hvorfor
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i ifølge igjen ikke ingen inn
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ja jeg
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kamp kampen kan kl klart kom komme kommer kontakt kort kroner kunne kveld
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kvinner
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la laget land landet langt leder ligger like litt løpet
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la laget land landet langt leder ligger like litt løpet lørdag
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man mange med meg mellom men mener mennesker mens mer mot mye må mål måtte
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man mandag mange mannen mars med meg mellom men mener menn mennesker mens mer
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millioner minutter mot msci mye må mål måtte
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ned neste noe noen nok ny nye nå når
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ned neste noe noen nok norge norsk norske ntb ny nye nå når
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og også om opp opplyser oss over
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og også om onsdag opp opplyser oslo oss over
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personer plass poeng på
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personer plass poeng politidistrikt politiet president prosent på
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runde rundt
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regjeringen runde rundt russland
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sa saken samme sammen samtidig satt se seg seks selv senere ser sett
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sa saken samme sammen samtidig satt se seg seks selv senere september ser sett
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siden sier sin sine siste sitt skal skriver skulle slik som sted stedet stor
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store står svært så
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store står sverige svært så søndag
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ta tatt tid tidligere til tilbake tillegg tok tror
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ta tatt tid tidligere til tilbake tillegg tirsdag to tok torsdag tre tror
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tyskland
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under ut uten utenfor
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under usa ut uten utenfor
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vant var ved veldig vi videre viktig vil ville viser vår være vært
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@ -1,10 +1,13 @@
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# Source: https://github.com/stopwords-iso/stopwords-sl
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# Removed various words that are not normally considered stop words, such as months.
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# TODO: probably needs to be tidied up – the list seems to have month names in
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# it, which shouldn't be considered stop words.
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STOP_WORDS = set(
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"""
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a
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ali
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april
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avgust
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b
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bi
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bil
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@ -16,6 +19,7 @@ biti
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blizu
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bo
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bodo
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bojo
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bolj
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bom
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bomo
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@ -33,6 +37,16 @@ da
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daleč
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dan
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danes
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datum
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december
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deset
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deseta
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deseti
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deseto
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devet
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deveta
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deveti
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deveto
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do
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dober
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dobra
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@ -40,7 +54,16 @@ dobri
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dobro
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dokler
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dol
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dolg
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dolga
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dolgi
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dovolj
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drug
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druga
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drugi
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drugo
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dva
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dve
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e
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eden
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en
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@ -51,6 +74,7 @@ enkrat
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eno
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etc.
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f
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februar
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g
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g.
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ga
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@ -69,12 +93,16 @@ iv
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ix
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iz
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j
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januar
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jaz
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je
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ji
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jih
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jim
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jo
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julij
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junij
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jutri
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k
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kadarkoli
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kaj
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|
@ -95,23 +123,41 @@ kje
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kjer
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kjerkoli
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ko
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koder
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koderkoli
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koga
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komu
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kot
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kratek
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kratka
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kratke
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kratki
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l
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lahka
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lahke
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lahki
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lahko
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le
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lep
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lepa
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lepe
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lepi
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lepo
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leto
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m
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maj
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majhen
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majhna
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majhni
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malce
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malo
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manj
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marec
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me
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med
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medtem
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mene
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mesec
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mi
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midva
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midve
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||||
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|
@ -137,6 +183,7 @@ najmanj
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naju
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največ
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nam
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narobe
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nas
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nato
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||||
nazaj
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|
|
@ -145,6 +192,7 @@ naša
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naše
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ne
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nedavno
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nedelja
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nek
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neka
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||||
nekaj
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||||
|
|
@ -188,6 +236,7 @@ njuna
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njuno
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||||
no
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nocoj
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november
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npr.
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o
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||||
ob
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||||
|
|
@ -195,23 +244,51 @@ oba
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|||
obe
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oboje
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od
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odprt
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||||
odprta
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||||
odprti
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||||
okoli
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||||
oktober
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||||
on
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||||
onadva
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||||
one
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||||
oni
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onidve
|
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osem
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||||
osma
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||||
osmi
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||||
osmo
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||||
oz.
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||||
p
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||||
pa
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||||
pet
|
||||
peta
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||||
petek
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||||
peti
|
||||
peto
|
||||
po
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||||
pod
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pogosto
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poleg
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poln
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polna
|
||||
polni
|
||||
polno
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ponavadi
|
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ponedeljek
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ponovno
|
||||
potem
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povsod
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pozdravljen
|
||||
pozdravljeni
|
||||
prav
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||||
prava
|
||||
prave
|
||||
pravi
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||||
pravo
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||||
prazen
|
||||
prazna
|
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prazno
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prbl.
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precej
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pred
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||||
|
|
@ -220,10 +297,19 @@ preko
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|||
pri
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||||
pribl.
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približno
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primer
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||||
pripravljen
|
||||
pripravljena
|
||||
pripravljeni
|
||||
proti
|
||||
prva
|
||||
prvi
|
||||
prvo
|
||||
r
|
||||
ravno
|
||||
redko
|
||||
res
|
||||
reč
|
||||
s
|
||||
saj
|
||||
sam
|
||||
|
|
@ -235,17 +321,29 @@ se
|
|||
sebe
|
||||
sebi
|
||||
sedaj
|
||||
sedem
|
||||
sedma
|
||||
sedmi
|
||||
sedmo
|
||||
sem
|
||||
september
|
||||
seveda
|
||||
si
|
||||
sicer
|
||||
skoraj
|
||||
skozi
|
||||
slab
|
||||
smo
|
||||
so
|
||||
sobota
|
||||
spet
|
||||
sreda
|
||||
srednja
|
||||
srednji
|
||||
sta
|
||||
ste
|
||||
stran
|
||||
stvar
|
||||
sva
|
||||
t
|
||||
ta
|
||||
|
|
@ -260,6 +358,10 @@ te
|
|||
tebe
|
||||
tebi
|
||||
tega
|
||||
težak
|
||||
težka
|
||||
težki
|
||||
težko
|
||||
ti
|
||||
tista
|
||||
tiste
|
||||
|
|
@ -269,6 +371,11 @@ tj.
|
|||
tja
|
||||
to
|
||||
toda
|
||||
torek
|
||||
tretja
|
||||
tretje
|
||||
tretji
|
||||
tri
|
||||
tu
|
||||
tudi
|
||||
tukaj
|
||||
|
|
@ -285,6 +392,10 @@ vaša
|
|||
vaše
|
||||
ve
|
||||
vedno
|
||||
velik
|
||||
velika
|
||||
veliki
|
||||
veliko
|
||||
vendar
|
||||
ves
|
||||
več
|
||||
|
|
@ -292,6 +403,10 @@ vi
|
|||
vidva
|
||||
vii
|
||||
viii
|
||||
visok
|
||||
visoka
|
||||
visoke
|
||||
visoki
|
||||
vsa
|
||||
vsaj
|
||||
vsak
|
||||
|
|
@ -305,21 +420,34 @@ vsega
|
|||
vsi
|
||||
vso
|
||||
včasih
|
||||
včeraj
|
||||
x
|
||||
z
|
||||
za
|
||||
zadaj
|
||||
zadnji
|
||||
zakaj
|
||||
zaprta
|
||||
zaprti
|
||||
zaprto
|
||||
zdaj
|
||||
zelo
|
||||
zunaj
|
||||
č
|
||||
če
|
||||
često
|
||||
četrta
|
||||
četrtek
|
||||
četrti
|
||||
četrto
|
||||
čez
|
||||
čigav
|
||||
š
|
||||
šest
|
||||
šesta
|
||||
šesti
|
||||
šesto
|
||||
štiri
|
||||
ž
|
||||
že
|
||||
""".split()
|
||||
|
|
|
|||
|
|
@ -155,11 +155,6 @@ def fr_tokenizer():
|
|||
return get_lang_class("fr")().tokenizer
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def fr_vocab():
|
||||
return get_lang_class("fr")().vocab
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def ga_tokenizer():
|
||||
return get_lang_class("ga")().tokenizer
|
||||
|
|
@ -210,11 +205,6 @@ def it_tokenizer():
|
|||
return get_lang_class("it")().tokenizer
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def it_vocab():
|
||||
return get_lang_class("it")().vocab
|
||||
|
||||
|
||||
@pytest.fixture(scope="session")
|
||||
def ja_tokenizer():
|
||||
pytest.importorskip("sudachipy")
|
||||
|
|
|
|||
|
|
@ -1,230 +1,8 @@
|
|||
from spacy.tokens import Doc
|
||||
import pytest
|
||||
|
||||
|
||||
# fmt: off
|
||||
@pytest.mark.parametrize(
|
||||
"words,heads,deps,pos,chunk_offsets",
|
||||
[
|
||||
# determiner + noun
|
||||
# un nom -> un nom
|
||||
(
|
||||
["un", "nom"],
|
||||
[1, 1],
|
||||
["det", "ROOT"],
|
||||
["DET", "NOUN"],
|
||||
[(0, 2)],
|
||||
),
|
||||
# determiner + noun starting with vowel
|
||||
# l'heure -> l'heure
|
||||
(
|
||||
["l'", "heure"],
|
||||
[1, 1],
|
||||
["det", "ROOT"],
|
||||
["DET", "NOUN"],
|
||||
[(0, 2)],
|
||||
),
|
||||
# determiner + plural noun
|
||||
# les romans -> les romans
|
||||
(
|
||||
["les", "romans"],
|
||||
[1, 1],
|
||||
["det", "ROOT"],
|
||||
["DET", "NOUN"],
|
||||
[(0, 2)],
|
||||
),
|
||||
# det + adj + noun
|
||||
# Le vieux Londres -> Le vieux Londres
|
||||
(
|
||||
['Les', 'vieux', 'Londres'],
|
||||
[2, 2, 2],
|
||||
["det", "amod", "ROOT"],
|
||||
["DET", "ADJ", "NOUN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# det + noun + adj
|
||||
# le nom propre -> le nom propre a proper noun
|
||||
(
|
||||
["le", "nom", "propre"],
|
||||
[1, 1, 1],
|
||||
["det", "ROOT", "amod"],
|
||||
["DET", "NOUN", "ADJ"],
|
||||
[(0, 3)],
|
||||
),
|
||||
# det + noun + adj plural
|
||||
# Les chiens bruns -> les chiens bruns
|
||||
(
|
||||
["Les", "chiens", "bruns"],
|
||||
[1, 1, 1],
|
||||
["det", "ROOT", "amod"],
|
||||
["DET", "NOUN", "ADJ"],
|
||||
[(0, 3)],
|
||||
),
|
||||
# multiple adjectives: one adj before the noun, one adj after the noun
|
||||
# un nouveau film intéressant -> un nouveau film intéressant
|
||||
(
|
||||
["un", "nouveau", "film", "intéressant"],
|
||||
[2, 2, 2, 2],
|
||||
["det", "amod", "ROOT", "amod"],
|
||||
["DET", "ADJ", "NOUN", "ADJ"],
|
||||
[(0,4)]
|
||||
),
|
||||
# multiple adjectives, both adjs after the noun
|
||||
# une personne intelligente et drôle -> une personne intelligente et drôle
|
||||
(
|
||||
["une", "personne", "intelligente", "et", "drôle"],
|
||||
[1, 1, 1, 4, 2],
|
||||
["det", "ROOT", "amod", "cc", "conj"],
|
||||
["DET", "NOUN", "ADJ", "CCONJ", "ADJ"],
|
||||
[(0,5)]
|
||||
),
|
||||
# relative pronoun
|
||||
# un bus qui va au ville -> un bus, qui, ville
|
||||
(
|
||||
['un', 'bus', 'qui', 'va', 'au', 'ville'],
|
||||
[1, 1, 3, 1, 5, 3],
|
||||
['det', 'ROOT', 'nsubj', 'acl:relcl', 'case', 'obl:arg'],
|
||||
['DET', 'NOUN', 'PRON', 'VERB', 'ADP', 'NOUN'],
|
||||
[(0,2), (2,3), (5,6)]
|
||||
),
|
||||
# relative subclause
|
||||
# Voilà la maison que nous voulons acheter -> la maison, nous That's the house that we want to buy.
|
||||
(
|
||||
['Voilà', 'la', 'maison', 'que', 'nous', 'voulons', 'acheter'],
|
||||
[0, 2, 0, 5, 5, 2, 5],
|
||||
['ROOT', 'det', 'obj', 'mark', 'nsubj', 'acl:relcl', 'xcomp'],
|
||||
['VERB', 'DET', 'NOUN', 'SCONJ', 'PRON', 'VERB', 'VERB'],
|
||||
[(1,3), (4,5)]
|
||||
),
|
||||
# Person name and title by flat
|
||||
# Louis XIV -> Louis XIV
|
||||
(
|
||||
["Louis", "XIV"],
|
||||
[0, 0],
|
||||
["ROOT", "flat:name"],
|
||||
["PROPN", "PROPN"],
|
||||
[(0,2)]
|
||||
),
|
||||
# Organization name by flat
|
||||
# Nations Unies -> Nations Unies
|
||||
(
|
||||
["Nations", "Unies"],
|
||||
[0, 0],
|
||||
["ROOT", "flat:name"],
|
||||
["PROPN", "PROPN"],
|
||||
[(0,2)]
|
||||
),
|
||||
# Noun compound, person name created by two flats
|
||||
# Louise de Bratagne -> Louise de Bratagne
|
||||
(
|
||||
["Louise", "de", "Bratagne"],
|
||||
[0, 0, 0],
|
||||
["ROOT", "flat:name", "flat:name"],
|
||||
["PROPN", "PROPN", "PROPN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# Noun compound, person name created by two flats
|
||||
# Louis François Joseph -> Louis François Joseph
|
||||
(
|
||||
["Louis", "François", "Joseph"],
|
||||
[0, 0, 0],
|
||||
["ROOT", "flat:name", "flat:name"],
|
||||
["PROPN", "PROPN", "PROPN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# one determiner + one noun + one adjective qualified by an adverb
|
||||
# quelques agriculteurs très riches -> quelques agriculteurs très riches
|
||||
(
|
||||
["quelques", "agriculteurs", "très", "riches"],
|
||||
[1, 1, 3, 1],
|
||||
['det', 'ROOT', 'advmod', 'amod'],
|
||||
['DET', 'NOUN', 'ADV', 'ADJ'],
|
||||
[(0,4)]
|
||||
),
|
||||
# Two NPs conjuncted
|
||||
# Il a un chien et un chat -> Il, un chien, un chat
|
||||
(
|
||||
['Il', 'a', 'un', 'chien', 'et', 'un', 'chat'],
|
||||
[1, 1, 3, 1, 6, 6, 3],
|
||||
['nsubj', 'ROOT', 'det', 'obj', 'cc', 'det', 'conj'],
|
||||
['PRON', 'VERB', 'DET', 'NOUN', 'CCONJ', 'DET', 'NOUN'],
|
||||
[(0,1), (2,4), (5,7)]
|
||||
|
||||
),
|
||||
# Two NPs together
|
||||
# l'écrivain brésilien Aníbal Machado -> l'écrivain brésilien, Aníbal Machado
|
||||
(
|
||||
["l'", 'écrivain', 'brésilien', 'Aníbal', 'Machado'],
|
||||
[1, 1, 1, 1, 3],
|
||||
['det', 'ROOT', 'amod', 'appos', 'flat:name'],
|
||||
['DET', 'NOUN', 'ADJ', 'PROPN', 'PROPN'],
|
||||
[(0, 3), (3, 5)]
|
||||
),
|
||||
# nmod relation between NPs
|
||||
# la destruction de la ville -> la destruction, la ville
|
||||
(
|
||||
['la', 'destruction', 'de', 'la', 'ville'],
|
||||
[1, 1, 4, 4, 1],
|
||||
['det', 'ROOT', 'case', 'det', 'nmod'],
|
||||
['DET', 'NOUN', 'ADP', 'DET', 'NOUN'],
|
||||
[(0,2), (3,5)]
|
||||
),
|
||||
# nmod relation between NPs
|
||||
# Archiduchesse d’Autriche -> Archiduchesse, Autriche
|
||||
(
|
||||
['Archiduchesse', 'd’', 'Autriche'],
|
||||
[0, 2, 0],
|
||||
['ROOT', 'case', 'nmod'],
|
||||
['NOUN', 'ADP', 'PROPN'],
|
||||
[(0,1), (2,3)]
|
||||
),
|
||||
# Compounding by nmod, several NPs chained together
|
||||
# la première usine de drogue du gouvernement -> la première usine, drogue, gouvernement
|
||||
(
|
||||
["la", "première", "usine", "de", "drogue", "du", "gouvernement"],
|
||||
[2, 2, 2, 4, 2, 6, 2],
|
||||
['det', 'amod', 'ROOT', 'case', 'nmod', 'case', 'nmod'],
|
||||
['DET', 'ADJ', 'NOUN', 'ADP', 'NOUN', 'ADP', 'NOUN'],
|
||||
[(0, 3), (4, 5), (6, 7)]
|
||||
),
|
||||
# several NPs
|
||||
# Traduction du rapport de Susana -> Traduction, rapport, Susana
|
||||
(
|
||||
['Traduction', 'du', 'raport', 'de', 'Susana'],
|
||||
[0, 2, 0, 4, 2],
|
||||
['ROOT', 'case', 'nmod', 'case', 'nmod'],
|
||||
['NOUN', 'ADP', 'NOUN', 'ADP', 'PROPN'],
|
||||
[(0,1), (2,3), (4,5)]
|
||||
|
||||
),
|
||||
# Several NPs
|
||||
# Le gros chat de Susana et son amie -> Le gros chat, Susana, son amie
|
||||
(
|
||||
['Le', 'gros', 'chat', 'de', 'Susana', 'et', 'son', 'amie'],
|
||||
[2, 2, 2, 4, 2, 7, 7, 2],
|
||||
['det', 'amod', 'ROOT', 'case', 'nmod', 'cc', 'det', 'conj'],
|
||||
['DET', 'ADJ', 'NOUN', 'ADP', 'PROPN', 'CCONJ', 'DET', 'NOUN'],
|
||||
[(0,3), (4,5), (6,8)]
|
||||
),
|
||||
# Passive subject
|
||||
# Les nouvelles dépenses sont alimentées par le grand compte bancaire de Clinton -> Les nouvelles dépenses, le grand compte bancaire, Clinton
|
||||
(
|
||||
['Les', 'nouvelles', 'dépenses', 'sont', 'alimentées', 'par', 'le', 'grand', 'compte', 'bancaire', 'de', 'Clinton'],
|
||||
[2, 2, 4, 4, 4, 8, 8, 8, 4, 8, 11, 8],
|
||||
['det', 'amod', 'nsubj:pass', 'aux:pass', 'ROOT', 'case', 'det', 'amod', 'obl:agent', 'amod', 'case', 'nmod'],
|
||||
['DET', 'ADJ', 'NOUN', 'AUX', 'VERB', 'ADP', 'DET', 'ADJ', 'NOUN', 'ADJ', 'ADP', 'PROPN'],
|
||||
[(0, 3), (6, 10), (11, 12)]
|
||||
)
|
||||
],
|
||||
)
|
||||
# fmt: on
|
||||
def test_fr_noun_chunks(fr_vocab, words, heads, deps, pos, chunk_offsets):
|
||||
doc = Doc(fr_vocab, words=words, heads=heads, deps=deps, pos=pos)
|
||||
assert [(c.start, c.end) for c in doc.noun_chunks] == chunk_offsets
|
||||
|
||||
|
||||
def test_noun_chunks_is_parsed_fr(fr_tokenizer):
|
||||
"""Test that noun_chunks raises Value Error for 'fr' language if Doc is not parsed."""
|
||||
doc = fr_tokenizer("Je suis allé à l'école")
|
||||
doc = fr_tokenizer("trouver des travaux antérieurs")
|
||||
with pytest.raises(ValueError):
|
||||
list(doc.noun_chunks)
|
||||
|
|
|
|||
|
|
@ -1,221 +0,0 @@
|
|||
from spacy.tokens import Doc
|
||||
import pytest
|
||||
|
||||
|
||||
# fmt: off
|
||||
@pytest.mark.parametrize(
|
||||
"words,heads,deps,pos,chunk_offsets",
|
||||
[
|
||||
# determiner + noun
|
||||
# un pollo -> un pollo
|
||||
(
|
||||
["un", "pollo"],
|
||||
[1, 1],
|
||||
["det", "ROOT"],
|
||||
["DET", "NOUN"],
|
||||
[(0,2)],
|
||||
),
|
||||
# two determiners + noun
|
||||
# il mio cane -> il mio cane
|
||||
(
|
||||
["il", "mio", "cane"],
|
||||
[2, 2, 2],
|
||||
["det", "det:poss", "ROOT"],
|
||||
["DET", "DET", "NOUN"],
|
||||
[(0,3)],
|
||||
),
|
||||
# two determiners, one is after noun. rare usage but still testing
|
||||
# il cane mio-> il cane mio
|
||||
(
|
||||
["il", "cane", "mio"],
|
||||
[1, 1, 1],
|
||||
["det", "ROOT", "det:poss"],
|
||||
["DET", "NOUN", "DET"],
|
||||
[(0,3)],
|
||||
),
|
||||
# relative pronoun
|
||||
# È molto bello il vestito che hai acquistat -> il vestito, che the dress that you bought is very pretty.
|
||||
(
|
||||
["È", "molto", "bello", "il", "vestito", "che", "hai", "acquistato"],
|
||||
[2, 2, 2, 4, 2, 7, 7, 4],
|
||||
['cop', 'advmod', 'ROOT', 'det', 'nsubj', 'obj', 'aux', 'acl:relcl'],
|
||||
['AUX', 'ADV', 'ADJ', 'DET', 'NOUN', 'PRON', 'AUX', 'VERB'],
|
||||
[(3,5), (5,6)]
|
||||
),
|
||||
# relative subclause
|
||||
# il computer che hai comprato -> il computer, che the computer that you bought
|
||||
(
|
||||
['il', 'computer', 'che', 'hai', 'comprato'],
|
||||
[1, 1, 4, 4, 1],
|
||||
['det', 'ROOT', 'nsubj', 'aux', 'acl:relcl'],
|
||||
['DET', 'NOUN', 'PRON', 'AUX', 'VERB'],
|
||||
[(0,2), (2,3)]
|
||||
),
|
||||
# det + noun + adj
|
||||
# Una macchina grande -> Una macchina grande
|
||||
(
|
||||
["Una", "macchina", "grande"],
|
||||
[1, 1, 1],
|
||||
["det", "ROOT", "amod"],
|
||||
["DET", "NOUN", "ADJ"],
|
||||
[(0,3)],
|
||||
),
|
||||
# noun + adj plural
|
||||
# mucche bianche
|
||||
(
|
||||
["mucche", "bianche"],
|
||||
[0, 0],
|
||||
["ROOT", "amod"],
|
||||
["NOUN", "ADJ"],
|
||||
[(0,2)],
|
||||
),
|
||||
# det + adj + noun
|
||||
# Una grande macchina -> Una grande macchina
|
||||
(
|
||||
['Una', 'grande', 'macchina'],
|
||||
[2, 2, 2],
|
||||
["det", "amod", "ROOT"],
|
||||
["DET", "ADJ", "NOUN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# det + adj + noun, det with apostrophe
|
||||
# un'importante associazione -> un'importante associazione
|
||||
(
|
||||
["Un'", 'importante', 'associazione'],
|
||||
[2, 2, 2],
|
||||
["det", "amod", "ROOT"],
|
||||
["DET", "ADJ", "NOUN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# multiple adjectives
|
||||
# Un cane piccolo e marrone -> Un cane piccolo e marrone
|
||||
(
|
||||
["Un", "cane", "piccolo", "e", "marrone"],
|
||||
[1, 1, 1, 4, 2],
|
||||
["det", "ROOT", "amod", "cc", "conj"],
|
||||
["DET", "NOUN", "ADJ", "CCONJ", "ADJ"],
|
||||
[(0,5)]
|
||||
),
|
||||
# determiner, adjective, compound created by flat
|
||||
# le Nazioni Unite -> le Nazioni Unite
|
||||
(
|
||||
["le", "Nazioni", "Unite"],
|
||||
[1, 1, 1],
|
||||
["det", "ROOT", "flat:name"],
|
||||
["DET", "PROPN", "PROPN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# one determiner + one noun + one adjective qualified by an adverb
|
||||
# alcuni contadini molto ricchi -> alcuni contadini molto ricchi some very rich farmers
|
||||
(
|
||||
['alcuni', 'contadini', 'molto', 'ricchi'],
|
||||
[1, 1, 3, 1],
|
||||
['det', 'ROOT', 'advmod', 'amod'],
|
||||
['DET', 'NOUN', 'ADV', 'ADJ'],
|
||||
[(0,4)]
|
||||
),
|
||||
# Two NPs conjuncted
|
||||
# Ho un cane e un gatto -> un cane, un gatto
|
||||
(
|
||||
['Ho', 'un', 'cane', 'e', 'un', 'gatto'],
|
||||
[0, 2, 0, 5, 5, 0],
|
||||
['ROOT', 'det', 'obj', 'cc', 'det', 'conj'],
|
||||
['VERB', 'DET', 'NOUN', 'CCONJ', 'DET', 'NOUN'],
|
||||
[(1,3), (4,6)]
|
||||
|
||||
),
|
||||
# Two NPs together
|
||||
# lo scrittore brasiliano Aníbal Machado -> lo scrittore brasiliano, Aníbal Machado
|
||||
(
|
||||
['lo', 'scrittore', 'brasiliano', 'Aníbal', 'Machado'],
|
||||
[1, 1, 1, 1, 3],
|
||||
['det', 'ROOT', 'amod', 'nmod', 'flat:name'],
|
||||
['DET', 'NOUN', 'ADJ', 'PROPN', 'PROPN'],
|
||||
[(0, 3), (3, 5)]
|
||||
),
|
||||
# Noun compound, person name and titles
|
||||
# Dom Pedro II -> Dom Pedro II
|
||||
(
|
||||
["Dom", "Pedro", "II"],
|
||||
[0, 0, 0],
|
||||
["ROOT", "flat:name", "flat:name"],
|
||||
["PROPN", "PROPN", "PROPN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# Noun compound created by flat
|
||||
# gli Stati Uniti
|
||||
(
|
||||
["gli", "Stati", "Uniti"],
|
||||
[1, 1, 1],
|
||||
["det", "ROOT", "flat:name"],
|
||||
["DET", "PROPN", "PROPN"],
|
||||
[(0,3)]
|
||||
),
|
||||
# nmod relation between NPs
|
||||
# la distruzione della città -> la distruzione, città
|
||||
(
|
||||
['la', 'distruzione', 'della', 'città'],
|
||||
[1, 1, 3, 1],
|
||||
['det', 'ROOT', 'case', 'nmod'],
|
||||
['DET', 'NOUN', 'ADP', 'NOUN'],
|
||||
[(0,2), (3,4)]
|
||||
),
|
||||
# Compounding by nmod, several NPs chained together
|
||||
# la prima fabbrica di droga del governo -> la prima fabbrica, droga, governo
|
||||
(
|
||||
["la", "prima", "fabbrica", "di", "droga", "del", "governo"],
|
||||
[2, 2, 2, 4, 2, 6, 2],
|
||||
['det', 'amod', 'ROOT', 'case', 'nmod', 'case', 'nmod'],
|
||||
['DET', 'ADJ', 'NOUN', 'ADP', 'NOUN', 'ADP', 'NOUN'],
|
||||
[(0, 3), (4, 5), (6, 7)]
|
||||
),
|
||||
# several NPs
|
||||
# Traduzione del rapporto di Susana -> Traduzione, rapporto, Susana
|
||||
(
|
||||
['Traduzione', 'del', 'rapporto', 'di', 'Susana'],
|
||||
[0, 2, 0, 4, 2],
|
||||
['ROOT', 'case', 'nmod', 'case', 'nmod'],
|
||||
['NOUN', 'ADP', 'NOUN', 'ADP', 'PROPN'],
|
||||
[(0,1), (2,3), (4,5)]
|
||||
|
||||
),
|
||||
# Several NPs
|
||||
# Il gatto grasso di Susana e la sua amica -> Il gatto grasso, Susana, sua amica
|
||||
(
|
||||
['Il', 'gatto', 'grasso', 'di', 'Susana', 'e', 'la', 'sua', 'amica'],
|
||||
[1, 1, 1, 4, 1, 8, 8, 8, 1],
|
||||
['det', 'ROOT', 'amod', 'case', 'nmod', 'cc', 'det', 'det:poss', 'conj'],
|
||||
['DET', 'NOUN', 'ADJ', 'ADP', 'PROPN', 'CCONJ', 'DET', 'DET', 'NOUN'],
|
||||
[(0,3), (4,5), (6,9)]
|
||||
),
|
||||
# Passive subject
|
||||
# La nuova spesa è alimentata dal grande conto in banca di Clinton -> Le nuova spesa, grande conto, banca, Clinton
|
||||
(
|
||||
['La', 'nuova', 'spesa', 'è', 'alimentata', 'dal', 'grande', 'conto', 'in', 'banca', 'di', 'Clinton'],
|
||||
[2, 2, 4, 4, 4, 7, 7, 4, 9, 7, 11, 9],
|
||||
['det', 'amod', 'nsubj:pass', 'aux:pass', 'ROOT', 'case', 'amod', 'obl:agent', 'case', 'nmod', 'case', 'nmod'],
|
||||
['DET', 'ADJ', 'NOUN', 'AUX', 'VERB', 'ADP', 'ADJ', 'NOUN', 'ADP', 'NOUN', 'ADP', 'PROPN'],
|
||||
[(0, 3), (6, 8), (9, 10), (11,12)]
|
||||
),
|
||||
# Misc
|
||||
# Ma mentre questo prestito possa ora sembrare gestibile, un improvviso cambiamento delle circostanze potrebbe portare a problemi di debiti -> questo prestiti, un provisso cambiento, circostanze, problemi, debiti
|
||||
(
|
||||
['Ma', 'mentre', 'questo', 'prestito', 'possa', 'ora', 'sembrare', 'gestibile', ',', 'un', 'improvviso', 'cambiamento', 'delle', 'circostanze', 'potrebbe', 'portare', 'a', 'problemi', 'di', 'debitii'],
|
||||
[15, 6, 3, 6, 6, 6, 15, 6, 6, 11, 11, 15, 13, 11, 15, 15, 17, 15, 19, 17],
|
||||
['cc', 'mark', 'det', 'nsubj', 'aux', 'advmod', 'advcl', 'xcomp', 'punct', 'det', 'amod', 'nsubj', 'case', 'nmod', 'aux', 'ROOT', 'case', 'obl', 'case', 'nmod'],
|
||||
['CCONJ', 'SCONJ', 'DET', 'NOUN', 'AUX', 'ADV', 'VERB', 'ADJ', 'PUNCT', 'DET', 'ADJ', 'NOUN', 'ADP', 'NOUN', 'AUX', 'VERB', 'ADP', 'NOUN', 'ADP', 'NOUN'],
|
||||
[(2,4), (9,12), (13,14), (17,18), (19,20)]
|
||||
)
|
||||
],
|
||||
)
|
||||
# fmt: on
|
||||
def test_it_noun_chunks(it_vocab, words, heads, deps, pos, chunk_offsets):
|
||||
doc = Doc(it_vocab, words=words, heads=heads, deps=deps, pos=pos)
|
||||
assert [(c.start, c.end) for c in doc.noun_chunks] == chunk_offsets
|
||||
|
||||
|
||||
def test_noun_chunks_is_parsed_it(it_tokenizer):
|
||||
"""Test that noun_chunks raises Value Error for 'it' language if Doc is not parsed."""
|
||||
doc = it_tokenizer("Sei andato a Oxford")
|
||||
with pytest.raises(ValueError):
|
||||
list(doc.noun_chunks)
|
||||
Loading…
Reference in New Issue
Block a user