relextract.py 文件源码

def ne_chunked():
    print()
    print("1500 Sentences from Penn Treebank, as processed by NLTK NE Chunker")
    print("=" * 45)
    ROLE = re.compile(r'.*(chairman|president|trader|scientist|economist|analyst|partner).*')
    rels = []
    for i, sent in enumerate(nltk.corpus.treebank.tagged_sents()[:1500]):
        sent = nltk.ne_chunk(sent)
        rels = extract_rels('PER', 'ORG', sent, corpus='ace', pattern=ROLE, window=7)
        for rel in rels:
            print('{0:<5}{1}'.format(i, rtuple(rel)))