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Analysis China time in sentence

Project description

简介

Time-NLP的python3版本
python 版本https://github.com/sunfiyes/Time-NLPY
Java 版本https://github.com/shinyke/Time-NLP

功能说明

用于句子中时间词的抽取和转换
详情请见test.py

res = tn.parse(target=u'过十分钟') # target为待分析语句,timeBase为基准时间默认是当前时间
print(res)
res = tn.parse(target=u'2013年二月二十八日下午四点三十分二十九秒', timeBase='2013-02-28 16:30:29') # target为待分析语句,timeBase为基准时间默认是当前时间
print(res)
res = tn.parse(target=u'我需要大概33天2分钟四秒', timeBase='2013-02-28 16:30:29') # target为待分析语句,timeBase为基准时间默认是当前时间
print(res)
res = tn.parse(target=u'今年儿童节晚上九点一刻') # target为待分析语句,timeBase为基准时间默认是当前时间
print(res)
res = tn.parse(target=u'2个小时以前') # target为待分析语句,timeBase为基准时间默认是当前时间
print(res)
res = tn.parse(target=u'晚上8点到上午10点之间') # target为待分析语句,timeBase为基准时间默认是当前时间
print(res)

返回结果:

{"timedelta": "0 days, 0:10:00", "type": "timedelta"}
{"timestamp": "2013-02-28 16:30:29", "type": "timestamp"}
{"type": "timedelta", "timedelta": {"year": 0, "month": 1, "day": 3, "hour": 0, "minute": 2, "second": 4}}
{"timestamp": "2018-06-01 21:15:00", "type": "timestamp"}
{"error": "no time pattern could be extracted."}
{"type": "timespan", "timespan": ["2018-03-16 20:00:00", "2018-03-16 10:00:00"]}

使用方式

demo:python3 Test.py

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