def asDict(sentence: Sentence, ngrams=2):
"""Convert a :class:`fnl.text.sentence.Sentence` into a feature dictionary."""
d = {'gene-count': sentence.countEntity('B-gene')}
stems = list(sentence.maskedStems())
pos = sentence.posTags()
tokens = Counter('{}/{}'.format(s, t) for s, t in zip(stems, pos))
d.update(tokens)
if "TARGET/NN" in d and "FACTOR/NN" in d:
d['has-all-entities'] = 1
gram = list(stems)
while ngrams > 1:
ngrams =- 1
tokens = Counter('{} {}'.format(s, g) for s, g in zip(stems, gram[1:]))
d.update(tokens)
return d
def asDict(sentence: Sentence, ngrams=2):
"""Convert a :class:`fnl.text.sentence.Sentence` into a feature dictionary."""
d = {'gene-count': sentence.countEntity('B-gene')}
stems = list(sentence.maskedStems())
pos = sentence.posTags()
tokens = Counter('{}/{}'.format(s, t) for s, t in zip(stems, pos))
d.update(tokens)
if "TARGET/NN" in d and "FACTOR/NN" in d:
d['has-all-entities'] = 1
gram = list(stems)
while ngrams > 1:
ngrams = -1
tokens = Counter('{} {}'.format(s, g) for s, g in zip(stems, gram[1:]))
d.update(tokens)
return d
