ontonotes.py 文件源码

python
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项目:allennlp 作者: allenai 项目源码 文件源码
def _process_coref_span_annotations_for_word(label: str,
                                                 word_index: int,
                                                 clusters: DefaultDict[int, List[Tuple[int, int]]],
                                                 coref_stacks: DefaultDict[int, List[int]]) -> None:
        """
        For a given coref label, add it to a currently open span(s), complete a span(s) or
        ignore it, if it is outside of all spans. This method mutates the clusters and coref_stacks
        dictionaries.

        Parameters
        ----------
        label : ``str``
            The coref label for this word.
        word_index : ``int``
            The word index into the sentence.
        clusters : ``DefaultDict[int, List[Tuple[int, int]]]``
            A dictionary mapping cluster ids to lists of inclusive spans into the
            sentence.
        coref_stacks: ``DefaultDict[int, List[int]]``
            Stacks for each cluster id to hold the start indices of active spans (spans
            which we are inside of when processing a given word). Spans with the same id
            can be nested, which is why we collect these opening spans on a stack, e.g:

            [Greg, the baker who referred to [himself]_ID1 as 'the bread man']_ID1
        """
        if label != "-":
            for segment in label.split("|"):
                # The conll representation of coref spans allows spans to
                # overlap. If spans end or begin at the same word, they are
                # separated by a "|".
                if segment[0] == "(":
                    # The span begins at this word.
                    if segment[-1] == ")":
                        # The span begins and ends at this word (single word span).
                        cluster_id = int(segment[1:-1])
                        clusters[cluster_id].append((word_index, word_index))
                    else:
                        # The span is starting, so we record the index of the word.
                        cluster_id = int(segment[1:])
                        coref_stacks[cluster_id].append(word_index)
                else:
                    # The span for this id is ending, but didn't start at this word.
                    # Retrieve the start index from the document state and
                    # add the span to the clusters for this id.
                    cluster_id = int(segment[:-1])
                    start = coref_stacks[cluster_id].pop()
                    clusters[cluster_id].append((start, word_index))
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