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			58 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			58 lines
		
	
	
		
			2.0 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| import pytest
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| 
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| from ...util import get_doc
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| 
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| 
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| def test_noun_chunks_is_parsed_sv(sv_tokenizer):
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|     """Test that noun_chunks raises Value Error for 'sv' language if Doc is not parsed.
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|     To check this test, we're constructing a Doc
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|     with a new Vocab here and forcing is_parsed to 'False'
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|     to make sure the noun chunks don't run.
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|     """
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|     doc = sv_tokenizer("Studenten läste den bästa boken")
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|     doc.is_parsed = False
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|     with pytest.raises(ValueError):
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|         list(doc.noun_chunks)
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| 
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| 
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| SV_NP_TEST_EXAMPLES = [
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|     (
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|         "En student läste en bok",  # A student read a book
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|         ["DET", "NOUN", "VERB", "DET", "NOUN"],
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|         ["det", "nsubj", "ROOT", "det", "dobj"],
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|         [1, 1, 0, 1, -2],
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|         ["En student", "en bok"],
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|     ),
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|     (
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|         "Studenten läste den bästa boken.",  # The student read the best book
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|         ["NOUN", "VERB", "DET", "ADJ", "NOUN", "PUNCT"],
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|         ["nsubj", "ROOT", "det", "amod", "dobj", "punct"],
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|         [1, 0, 2, 1, -3, -4],
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|         ["Studenten", "den bästa boken"],
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|     ),
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|     (
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|         "De samvetslösa skurkarna hade stulit de största juvelerna på söndagen",  # The remorseless crooks had stolen the largest jewels that sunday
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|         ["DET", "ADJ", "NOUN", "VERB", "VERB", "DET", "ADJ", "NOUN", "ADP", "NOUN"],
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|         ["det", "amod", "nsubj", "aux", "root", "det", "amod", "dobj", "case", "nmod"],
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|         [2, 1, 2, 1, 0, 2, 1, -3, 1, -5],
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|         ["De samvetslösa skurkarna", "de största juvelerna", "på söndagen"],
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|     ),
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| ]
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| 
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| 
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| @pytest.mark.parametrize(
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|     "text,pos,deps,heads,expected_noun_chunks", SV_NP_TEST_EXAMPLES
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| )
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| def test_sv_noun_chunks(sv_tokenizer, text, pos, deps, heads, expected_noun_chunks):
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|     tokens = sv_tokenizer(text)
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| 
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|     assert len(heads) == len(pos)
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|     doc = get_doc(
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|         tokens.vocab, words=[t.text for t in tokens], heads=heads, deps=deps, pos=pos
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|     )
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| 
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|     noun_chunks = list(doc.noun_chunks)
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|     assert len(noun_chunks) == len(expected_noun_chunks)
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|     for i, np in enumerate(noun_chunks):
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|         assert np.text == expected_noun_chunks[i]
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