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	* added it vocab * copied portuguese * added possessive determiner * added conjed Nps * added nmoded Nps * test misc * more examples * fixed typo * fixed parenth * fixed comma * comma fix * added syntax iters * fix some index problems * fixed index * corrected heads for test case * fixed tets case * fixed determiner gender * cleaned left over * added example with apostophe
		
			
				
	
	
		
			87 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			87 lines
		
	
	
		
			3.1 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
| from typing import Union, Iterator, Tuple
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| 
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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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| 
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| 
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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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| 
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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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| 
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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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| 
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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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| 
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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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| 
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| 
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| SYNTAX_ITERATORS = {"noun_chunks": noun_chunks}
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