mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-14 13:47:13 +03:00
78 lines
3.0 KiB
Python
78 lines
3.0 KiB
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
from ...util import get_doc
|
|
|
|
import pytest
|
|
|
|
|
|
def test_parser_noun_chunks_standard(en_tokenizer):
|
|
text = "A base phrase should be recognized."
|
|
heads = [2, 1, 3, 2, 1, 0, -1]
|
|
tags = ['DT', 'JJ', 'NN', 'MD', 'VB', 'VBN', '.']
|
|
deps = ['det', 'amod', 'nsubjpass', 'aux', 'auxpass', 'ROOT', 'punct']
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], tags=tags, deps=deps, heads=heads)
|
|
chunks = list(doc.noun_chunks)
|
|
assert len(chunks) == 1
|
|
assert chunks[0].text_with_ws == "A base phrase "
|
|
|
|
|
|
def test_parser_noun_chunks_coordinated(en_tokenizer):
|
|
text = "A base phrase and a good phrase are often the same."
|
|
heads = [2, 1, 5, -1, 2, 1, -4, 0, -1, 1, -3, -4]
|
|
tags = ['DT', 'NN', 'NN', 'CC', 'DT', 'JJ', 'NN', 'VBP', 'RB', 'DT', 'JJ', '.']
|
|
deps = ['det', 'compound', 'nsubj', 'cc', 'det', 'amod', 'conj', 'ROOT', 'advmod', 'det', 'attr', 'punct']
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], tags=tags, deps=deps, heads=heads)
|
|
chunks = list(doc.noun_chunks)
|
|
assert len(chunks) == 2
|
|
assert chunks[0].text_with_ws == "A base phrase "
|
|
assert chunks[1].text_with_ws == "a good phrase "
|
|
|
|
|
|
def test_parser_noun_chunks_pp_chunks(en_tokenizer):
|
|
text = "A phrase with another phrase occurs."
|
|
heads = [1, 4, -1, 1, -2, 0, -1]
|
|
tags = ['DT', 'NN', 'IN', 'DT', 'NN', 'VBZ', '.']
|
|
deps = ['det', 'nsubj', 'prep', 'det', 'pobj', 'ROOT', 'punct']
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], tags=tags, deps=deps, heads=heads)
|
|
chunks = list(doc.noun_chunks)
|
|
assert len(chunks) == 2
|
|
assert chunks[0].text_with_ws == "A phrase "
|
|
assert chunks[1].text_with_ws == "another phrase "
|
|
|
|
|
|
def test_parser_noun_chunks_appositional_modifiers(en_tokenizer):
|
|
text = "Sam, my brother, arrived to the house."
|
|
heads = [5, -1, 1, -3, -4, 0, -1, 1, -2, -4]
|
|
tags = ['NNP', ',', 'PRP$', 'NN', ',', 'VBD', 'IN', 'DT', 'NN', '.']
|
|
deps = ['nsubj', 'punct', 'poss', 'appos', 'punct', 'ROOT', 'prep', 'det', 'pobj', 'punct']
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], tags=tags, deps=deps, heads=heads)
|
|
chunks = list(doc.noun_chunks)
|
|
assert len(chunks) == 3
|
|
assert chunks[0].text_with_ws == "Sam "
|
|
assert chunks[1].text_with_ws == "my brother "
|
|
assert chunks[2].text_with_ws == "the house "
|
|
|
|
|
|
def test_parser_noun_chunks_dative(en_tokenizer):
|
|
text = "She gave Bob a raise."
|
|
heads = [1, 0, -1, 1, -3, -4]
|
|
tags = ['PRP', 'VBD', 'NNP', 'DT', 'NN', '.']
|
|
deps = ['nsubj', 'ROOT', 'dative', 'det', 'dobj', 'punct']
|
|
|
|
tokens = en_tokenizer(text)
|
|
doc = get_doc(tokens.vocab, [t.text for t in tokens], tags=tags, deps=deps, heads=heads)
|
|
chunks = list(doc.noun_chunks)
|
|
assert len(chunks) == 3
|
|
assert chunks[0].text_with_ws == "She "
|
|
assert chunks[1].text_with_ws == "Bob "
|
|
assert chunks[2].text_with_ws == "a raise "
|