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	* Clean up spacy.tokens * Update `set_children_from_heads`: * Don't check `dep` when setting lr_* or sentence starts * Set all non-sentence starts to `False` * Use `set_children_from_heads` in `Token.head` setter * Reduce similar/duplicate code (admittedly adds a bit of overhead) * Update sentence starts consistently * Remove unused `Doc.set_parse` * Minor changes: * Declare cython variables (to avoid cython warnings) * Clean up imports * Modify set_children_from_heads to set token range Modify `set_children_from_heads` so that it adjust tokens within a specified range rather then the whole document. Modify the `Token.head` setter to adjust only the tokens affected by the new head assignment.
		
			
				
	
	
		
			181 lines
		
	
	
		
			6.2 KiB
		
	
	
	
		
			Cython
		
	
	
	
	
	
			
		
		
	
	
			181 lines
		
	
	
		
			6.2 KiB
		
	
	
	
		
			Cython
		
	
	
	
	
	
# cython: profile=True, infer_types=True
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"""Implements the projectivize/deprojectivize mechanism in Nivre & Nilsson 2005
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for doing pseudo-projective parsing implementation uses the HEAD decoration
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scheme.
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"""
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from copy import copy
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from ...tokens.doc cimport Doc, set_children_from_heads
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from ...errors import Errors
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DELIMITER = '||'
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def ancestors(tokenid, heads):
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    # Returns all words going from the word up the path to the root. The path
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    # to root cannot be longer than the number of words in the  sentence. This
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    # function ends after at most len(heads) steps, because it would otherwise
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    # loop indefinitely on cycles.
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    head = tokenid
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    cnt = 0
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    while heads[head] != head and cnt < len(heads):
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        head = heads[head]
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        cnt += 1
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        yield head
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        if head is None:
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            break
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def contains_cycle(heads):
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    # in an acyclic tree, the path from each word following the head relation
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    # upwards always ends at the root node
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    for tokenid in range(len(heads)):
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        seen = set([tokenid])
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        for ancestor in ancestors(tokenid, heads):
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            if ancestor in seen:
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                return seen
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            seen.add(ancestor)
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    return None
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def is_nonproj_arc(tokenid, heads):
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    # definition (e.g. Havelka 2007): an arc h -> d, h < d is non-projective
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    # if there is a token k, h < k < d such that h is not
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    # an ancestor of k. Same for h -> d, h > d
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    head = heads[tokenid]
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    if head == tokenid:  # root arcs cannot be non-projective
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        return False
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    elif head is None:  # unattached tokens cannot be non-projective
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        return False
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    cdef int start, end
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    if head < tokenid:
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        start, end = (head+1, tokenid)
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    else:
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        start, end = (tokenid+1, head)
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    for k in range(start, end):
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        for ancestor in ancestors(k, heads):
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            if ancestor is None:  # for unattached tokens/subtrees
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                break
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            elif ancestor == head:  # normal case: k dominated by h
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                break
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        else:  # head not in ancestors: d -> h is non-projective
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            return True
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    return False
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def is_nonproj_tree(heads):
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    # a tree is non-projective if at least one arc is non-projective
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    return any(is_nonproj_arc(word, heads) for word in range(len(heads)))
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def decompose(label):
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    return label.partition(DELIMITER)[::2]
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def is_decorated(label):
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    return DELIMITER in label
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def count_decorated_labels(gold_data):
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    freqs = {}
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    for example in gold_data:
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        proj_heads, deco_deps = projectivize(example.get_aligned("HEAD"),
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                                             example.get_aligned("DEP"))
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        # set the label to ROOT for each root dependent
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        deco_deps = ['ROOT' if head == i else deco_deps[i]
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                       for i, head in enumerate(proj_heads)]
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        # count label frequencies
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        for label in deco_deps:
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            if is_decorated(label):
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                freqs[label] = freqs.get(label, 0) + 1
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    return freqs
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def projectivize(heads, labels):
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    # Use the algorithm by Nivre & Nilsson 2005. Assumes heads to be a proper
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    # tree, i.e. connected and cycle-free. Returns a new pair (heads, labels)
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    # which encode a projective and decorated tree.
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    proj_heads = copy(heads)
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    smallest_np_arc = _get_smallest_nonproj_arc(proj_heads)
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    if smallest_np_arc is None:  # this sentence is already projective
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        return proj_heads, copy(labels)
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    while smallest_np_arc is not None:
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        _lift(smallest_np_arc, proj_heads)
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        smallest_np_arc = _get_smallest_nonproj_arc(proj_heads)
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    deco_labels = _decorate(heads, proj_heads, labels)
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    return proj_heads, deco_labels
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cpdef deprojectivize(Doc doc):
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    # Reattach arcs with decorated labels (following HEAD scheme). For each
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    # decorated arc X||Y, search top-down, left-to-right, breadth-first until
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    # hitting a Y then make this the new head.
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    for i in range(doc.length):
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        label = doc.vocab.strings[doc.c[i].dep]
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        if DELIMITER in label:
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            new_label, head_label = label.split(DELIMITER)
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            new_head = _find_new_head(doc[i], head_label)
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            doc.c[i].head = new_head.i - i
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            doc.c[i].dep = doc.vocab.strings.add(new_label)
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    set_children_from_heads(doc.c, 0, doc.length)
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    return doc
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def _decorate(heads, proj_heads, labels):
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    # uses decoration scheme HEAD from Nivre & Nilsson 2005
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    if (len(heads) != len(proj_heads)) or (len(proj_heads) != len(labels)):
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        raise ValueError(Errors.E082.format(n_heads=len(heads),
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                                            n_proj_heads=len(proj_heads),
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                                            n_labels=len(labels)))
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    deco_labels = []
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    for tokenid, head in enumerate(heads):
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        if head != proj_heads[tokenid]:
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            deco_labels.append(f"{labels[tokenid]}{DELIMITER}{labels[head]}")
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        else:
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            deco_labels.append(labels[tokenid])
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    return deco_labels
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def _get_smallest_nonproj_arc(heads):
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    # return the smallest non-proj arc or None
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    # where size is defined as the distance between dep and head
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    # and ties are broken left to right
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    smallest_size = float('inf')
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    smallest_np_arc = None
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    for tokenid, head in enumerate(heads):
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        size = abs(tokenid-head)
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        if size < smallest_size and is_nonproj_arc(tokenid, heads):
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            smallest_size = size
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            smallest_np_arc = tokenid
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    return smallest_np_arc
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def _lift(tokenid, heads):
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    # reattaches a word to it's grandfather
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    head = heads[tokenid]
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    ghead = heads[head]
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    # attach to ghead if head isn't attached to root else attach to root
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    heads[tokenid] = ghead if head != ghead else tokenid
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def _find_new_head(token, headlabel):
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    # search through the tree starting from the head of the given token
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    # returns the id of the first descendant with the given label
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    # if there is none, return the current head (no change)
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    queue = [token.head]
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    while queue:
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        next_queue = []
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        for qtoken in queue:
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            for child in qtoken.children:
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                if child.is_space:
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                    continue
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                if child == token:
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                    continue
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                if child.dep_ == headlabel:
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                    return child
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                next_queue.append(child)
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        queue = next_queue
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    return token.head
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