命名实体识别，使用pyltp提取文本中的地址

首先安装pyltp

pytlp项目首页

单例类（第一次调用时加载模型）

class Singleton(object):

    def __new__(cls, *args, **kwargs):

        if not hasattr(cls, '_the_instance'):

            cls._the_instance = object.__new__(cls, *args, **kwargs)

        return cls._the_instance

使用pyltp提取地址

import os

from pyltp import Segmentor, Postagger, NamedEntityRecognizer

from main.models.Singleton import Singleton

class address_extract_model(Singleton):

    print('load ltp model start...')

    pwd = os.getcwd()

    project_path = os.path.abspath(os.path.dirname(pwd) + os.path.sep + ".")

    LTP_DATA_DIR = project_path + '\AlarmClassification\main\ltp\model'  # ltp模型目录的路径

    cws_model_path = os.path.join(LTP_DATA_DIR, 'cws.model')

    pos_model_path = os.path.join(LTP_DATA_DIR, 'pos.model')  # 词性标注模型路径，模型名称为`pos.model`

    ner_model_path = os.path.join(LTP_DATA_DIR, 'ner.model')  # 命名实体识别模型路径，模型名称为`ner.model`

    print('path' + cws_model_path)

    segmentor = Segmentor()  # 初始化实例

    segmentor.load(cws_model_path)  # 加载模型

    postagger = Postagger() # 初始化实例

    postagger.load(pos_model_path)  # 加载模型

    recognizer = NamedEntityRecognizer() # 初始化实例

    recognizer.load(ner_model_path)  # 加载模型

    def get_model(self):

        return self.segmentor, self.postagger, self.recognizer

def get_address_prediction(alarm_content):

    model = address_extract_model()

    segmentor, postagger, recognizer = model.get_model()

    words = segmentor.segment(alarm_content)  # 分词

    postags = postagger.postag(words)  # 词性标注

    netags = recognizer.recognize(words, postags)  # 命名实体识别

    result = ''

    for i in range(0, len(netags)):

        print(words[i] + ': ' + netags[i])

        # 地名标签为 ns

        if 's' in netags[i]:

            result += words[i] + ','

    if len(result) < 1:

        result = 'No address!'

    print(result)

    return result

def get_address(alarm_content):

    print("start get_address...")

    result = "Exception"

    try:

        result = get_address_prediction(alarm_content)

    except Exception as ex:

        print(ex)

    print("Output is " + result)

    return result

# segmentor.release()  # 释放模型

# postagger.release()

# recognizer.release()

运行效果

项目源码 ( 命名实体提取代码位于main/ltp， 模型文件需要到pyltp下载 )

https://github.com/haibincoder/AlarmClassification

命名实体识别，使用pyltp提取文本中的地址的相关教程结束。