streamcorpus_pipeline/_taggers.py
def make_chains_with_names(sentences):
    '''
    assemble in-doc coref chains by mapping equiv_id to tokens and
    their cleansed name strings

    :param sentences: iterator over token generators
    :returns dict:
        keys are equiv_ids,
        values are tuple(concatentated name string, list of tokens)
    '''
    ## if an equiv_id is -1, then the token is classified into some
    ## entity_type but has not other tokens in its chain.  We don't
    ## want these all lumped together, so we give them distinct "fake"
    ## equiv_id other than -1 -- counting negatively to avoid
    ## collisions with "real" equiv_ids
    fake_equiv_ids = -2

    ## use a default dictionary
    equiv_ids = collections.defaultdict(lambda: (set(), set()))

    for tagger_id, sents in sentences.items():
        for sent in sents:
            for tok in sent.tokens:
                if tok.entity_type is not None:

                    ## get an appropriate equiv_id
                    if tok.equiv_id == -1:
                        eqid = fake_equiv_ids
                        fake_equiv_ids -= 1
                    else:
                        eqid = tok.equiv_id

                    ## store the name parts initially as a set
                    equiv_ids[eqid][0].add(cleanse(tok.token.decode('utf8')))
                    ## carry a *reference* to the entire Token object
                    equiv_ids[eqid][1].add(tok)

    return equiv_ids
def make_chains_with_names(sentences):
    '''
    assemble in-doc coref chains by mapping equiv_id to tokens and
    their cleansed name strings

    :param sentences: iterator over token generators
    :returns dict:
        keys are equiv_ids,
        values are tuple(concatentated name string, list of tokens)
    '''
    ## if an equiv_id is -1, then the token is classified into some
    ## entity_type but has not other tokens in its chain.  We don't
    ## want these all lumped together, so we give them distinct "fake"
    ## equiv_id other than -1 -- counting negatively to avoid
    ## collisions with "real" equiv_ids
    fake_equiv_ids = -2

    ## use a default dictionary
    equiv_ids = collections.defaultdict(lambda: (set(), set()))

    for tagger_id, sents in sentences.items():
        for sent in sents:
            for tok in sent.tokens:
                if tok.entity_type is not None:

                    ## get an appropriate equiv_id
                    if tok.equiv_id == -1:
                        eqid = fake_equiv_ids
                        fake_equiv_ids -= 1
                    else:
                        eqid = tok.equiv_id

                    ## store the name parts initially as a set
                    equiv_ids[eqid][0].add(cleanse(tok.token.decode('utf8')))
                    ## carry a *reference* to the entire Token object
                    equiv_ids[eqid][1].add(tok)

    return equiv_ids
def make_chains_with_names ( sentences ) : ## if an equiv_id is -1, then the token is classified into some ## entity_type but has not other tokens in its chain.  We don't ## want these all lumped together, so we give them distinct "fake" ## equiv_id other than -1 -- counting negatively to avoid ## collisions with "real" equiv_ids fake_equiv_ids = - 2 ## use a default dictionary equiv_ids = collections . defaultdict ( lambda : ( set ( ) , set ( ) ) ) for tagger_id , sents in sentences . items ( ) : for sent in sents : for tok in sent . tokens : if tok . entity_type is not None : ## get an appropriate equiv_id if tok . equiv_id == - 1 : eqid = fake_equiv_ids fake_equiv_ids -= 1 else : eqid = tok . equiv_id ## store the name parts initially as a set equiv_ids [ eqid ] [ 0 ] . add ( cleanse ( tok . token . decode ( 'utf8' ) ) ) ## carry a *reference* to the entire Token object equiv_ids [ eqid ] [ 1 ] . add ( tok ) return equiv_ids
assemble in-doc coref chains by mapping equiv_id to tokens and
    their cleansed name strings

    :param sentences: iterator over token generators
    :returns dict:
        keys are equiv_ids,
        values are tuple(concatentated name string, list of tokens)
assemble in - doc coref chains by mapping equiv_id to tokens and their cleansed name strings