简单命名实体识别

使用pyhanlp包识别命名实体（机构名，地名）

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from pyhanlp import *
# 目标词性列表
# nt: 机构团体名
# ns: 地名
# nsf: 音译地名
part_of_speech_list = ['nt', 'ns', 'nsf']


# 判断是否为中文单词
# 汉字编码范围\u4E00-\u9FA5
def is_all_chinese(strs):
    flag = True
    for ch in strs:
        if not '\u4e00' <= ch <= '\u9fa5':
            flag = False
    return flag


def get_black_list():
    black_list = []
    with open('./blacklist') as f:
        for line in f:
            line = line.strip()
            if line not in black_list:
                black_list.append(line)
    return black_list


black_list = get_black_list()


def entity_recognition(sentence):
    entity = []
    NLPTokenizer = JClass("com.hankcs.hanlp.tokenizer.NLPTokenizer")
    term_list = NLPTokenizer.segment(sentence)
    for term in term_list:
        word = term.word
        nature = str(term.nature)

        if (len(word) < 2) or (nature not in part_of_speech_list) \
                or (word in black_list) or (word in entity):
            continue
        flag = is_all_chinese(word)
        if not flag:
            continue
        entity.append(word)

    return "|".join(entity)


if __name__ == "__main__":
    text = '北约多国海军参加的“海上微风2021”演习已经开始，不过公开信息显示，美国派出的“罗斯”号导弹驱逐舰还窝在乌克兰港口，而英国士兵则在社交媒体上晒乌克兰方面供应的单调饮食，似乎颇有不满。'
    tags = entity_recognition(text)
    print(tags)