qa.py 文件源码

def whereRules(sentenceOriginal):
    score = 0
    sentence = sentenceOriginal.lower()

    # for chunk in nltk.ne_chunk(nltk.pos_tag(nltk.word_tokenize(sentenceOriginal))):
    #         if type(chunk) is nltk.tree.Tree:
    #             if 'LOCATION' in chunk.label() or 'GPE' in chunk.label():
    #                 score += 10

    # RULE 2
    for word in LOCPREP:
        if word in sentence:
            score += 4

    # RULE 3
    for word in LOCATION:
        if word in sentence:
            score += 6

    return score

# WHEN RULES