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	Adding noun_chunks to the Swedish language model (sv) (#4422)
* Create syntax_iterators.py Replica of spacy/lang/fr/syntax_iterators.py * Added import statements for SYNTAX_ITERATORS * Create gustavengstrom.md * Added "dobj" to list of labels in noun_chunks method and a test_noun_chunks method to the Swedish language model. * Delete README-checkpoint.md Co-authored-by: Gustav <gustav@davcon.se> Co-authored-by: Ines Montani <ines@ines.io>
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							|  | @ -0,0 +1,106 @@ | |||
| # spaCy contributor agreement | ||||
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 | ||||
| ## Contributor Details | ||||
| 
 | ||||
| | Field                          | Entry                | | ||||
| |------------------------------- | -------------------- | | ||||
| | Name                           | Gustav Engström      | | ||||
| | Company name (if applicable)   | Davcon               | | ||||
| | Title or role (if applicable)  | Data scientis        | | ||||
| | Date                           | 2019-10-10           | | ||||
| | GitHub username                | gustavengstrom       | | ||||
| | Website (optional)             |                      | | ||||
|  | @ -14,6 +14,7 @@ from ..norm_exceptions import BASE_NORMS | |||
| from ...language import Language | ||||
| from ...attrs import LANG, NORM | ||||
| from ...util import update_exc, add_lookups | ||||
| from .syntax_iterators import SYNTAX_ITERATORS | ||||
| 
 | ||||
| 
 | ||||
| class SwedishDefaults(Language.Defaults): | ||||
|  | @ -29,6 +30,7 @@ class SwedishDefaults(Language.Defaults): | |||
|     suffixes = TOKENIZER_SUFFIXES | ||||
|     stop_words = STOP_WORDS | ||||
|     morph_rules = MORPH_RULES | ||||
|     syntax_iterators = SYNTAX_ITERATORS | ||||
| 
 | ||||
| 
 | ||||
| class Swedish(Language): | ||||
|  |  | |||
							
								
								
									
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| # coding: utf8 | ||||
| from __future__ import unicode_literals | ||||
| 
 | ||||
| from ...symbols import NOUN, PROPN, PRON | ||||
| 
 | ||||
| 
 | ||||
| def noun_chunks(obj): | ||||
|     """ | ||||
|     Detect base noun phrases from a dependency parse. Works on both Doc and Span. | ||||
|     """ | ||||
|     labels = [ | ||||
|         "nsubj", | ||||
|         "nsubj:pass", | ||||
|         "dobj", | ||||
|         "obj", | ||||
|         "iobj", | ||||
|         "ROOT", | ||||
|         "appos", | ||||
|         "nmod", | ||||
|         "nmod:poss", | ||||
|     ] | ||||
|     doc = obj.doc  # Ensure works on both Doc and Span. | ||||
|     np_deps = [doc.vocab.strings[label] for label in labels] | ||||
|     conj = doc.vocab.strings.add("conj") | ||||
|     np_label = doc.vocab.strings.add("NP") | ||||
|     seen = set() | ||||
|     for i, word in enumerate(obj): | ||||
|         if word.pos not in (NOUN, PROPN, PRON): | ||||
|             continue | ||||
|         # Prevent nested chunks from being produced | ||||
|         if word.i in seen: | ||||
|             continue | ||||
|         if word.dep in np_deps: | ||||
|             if any(w.i in seen for w in word.subtree): | ||||
|                 continue | ||||
|             seen.update(j for j in range(word.left_edge.i, word.right_edge.i + 1)) | ||||
|             yield word.left_edge.i, word.right_edge.i + 1, np_label | ||||
|         elif word.dep == conj: | ||||
|             head = word.head | ||||
|             while head.dep == conj and head.head.i < head.i: | ||||
|                 head = head.head | ||||
|             # If the head is an NP, and we're coordinated to it, we're an NP | ||||
|             if head.dep in np_deps: | ||||
|                 if any(w.i in seen for w in word.subtree): | ||||
|                     continue | ||||
|                 seen.update(j for j in range(word.left_edge.i, word.right_edge.i + 1)) | ||||
|                 yield word.left_edge.i, word.right_edge.i + 1, np_label | ||||
| 
 | ||||
| 
 | ||||
| SYNTAX_ITERATORS = {"noun_chunks": noun_chunks} | ||||
							
								
								
									
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							|  | @ -0,0 +1,48 @@ | |||
| # coding: utf-8 | ||||
| from __future__ import unicode_literals | ||||
| 
 | ||||
| import pytest | ||||
| from spacy.lang.sv.syntax_iterators import SYNTAX_ITERATORS | ||||
| from ...util import get_doc | ||||
| 
 | ||||
| SV_NP_TEST_EXAMPLES = [ | ||||
|     ( | ||||
|         "En student läste en bok",  # A student read a book | ||||
|         ["DET", "NOUN", "VERB", "DET", "NOUN"], | ||||
|         ["det", "nsubj", "ROOT", "det", "dobj"], | ||||
|         [1, 1, 0, 1, -2], | ||||
|         ["En student", "en bok"], | ||||
|     ), | ||||
|     ( | ||||
|         "Studenten läste den bästa boken.",  # The student read the best book | ||||
|         ["NOUN", "VERB", "DET", "ADJ", "NOUN", "PUNCT"], | ||||
|         ["nsubj", "ROOT", "det", "amod", "dobj", "punct"], | ||||
|         [1, 0, 2, 1, -3, -4], | ||||
|         ["Studenten", "den bästa boken"], | ||||
|     ), | ||||
|     ( | ||||
|         "De samvetslösa skurkarna hade stulit de största juvelerna på söndagen",  # The remorseless crooks had stolen the largest jewels that sunday | ||||
|         ["DET", "ADJ", "NOUN", "VERB", "VERB", "DET", "ADJ", "NOUN", "ADP", "NOUN"], | ||||
|         ["det", "amod", "nsubj", "aux", "root", "det", "amod", "dobj", "case", "nmod"], | ||||
|         [2, 1, 2, 1, 0, 2, 1, -3, 1, -5], | ||||
|         ["De samvetslösa skurkarna", "de största juvelerna", "på söndagen"], | ||||
|     ), | ||||
| ] | ||||
| 
 | ||||
| 
 | ||||
| @pytest.mark.parametrize( | ||||
|     "text,pos,deps,heads,expected_noun_chunks", SV_NP_TEST_EXAMPLES | ||||
| ) | ||||
| def test_sv_noun_chunks(sv_tokenizer, text, pos, deps, heads, expected_noun_chunks): | ||||
|     tokens = sv_tokenizer(text) | ||||
| 
 | ||||
|     assert len(heads) == len(pos) | ||||
|     doc = get_doc( | ||||
|         tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps, pos=pos | ||||
|     ) | ||||
| 
 | ||||
|     noun_chunks = list(doc.noun_chunks) | ||||
|     assert len(noun_chunks) == len(expected_noun_chunks) | ||||
|     for i, np in enumerate(noun_chunks): | ||||
|         assert np.text == expected_noun_chunks[i] | ||||
| 
 | ||||
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