Open hailiang-wang opened 6 years ago
依存关系主要使用句法分析器完成,句法分析器也有基于规则的和基于机器学习训练的。 虽然实现方案不同,但是二者的模型输出的是同样一个规范: https://nlp.stanford.edu/software/lex-parser.shtml
目前,state of art的可以参考 http://nlp.qq.com/semantic.cgi 句法类API
https://my.oschina.net/dingdayu/blog/1083438
https://github.com/dsindex/syntaxnet/issues/24
https://www.jianshu.com/p/479a111ed5f4
http://www.hankcs.com/nlp/to-achieve-a-simple-generative-dependency-parsing.html
http://www.hankcs.com/nlp/parsing/neural-network-based-dependency-parser.html
论文分析 https://www.zhihu.com/question/46272554 https://arxiv.org/pdf/1603.06042v1.pdf
https://gist.github.com/Samurais/2c935182fb7213205284f7cd5040536a https://github.com/Xe0n0/python-dependency-parser
http://demo.clab.cs.cmu.edu/fa2015-11711/images/b/b1/TbparsingSmallCorrection.pdf https://www.youtube.com/results?search_query=Greedy+Transition-Based+Parsing
https://jiaxuncai.github.io/2016/10/30/%E4%BE%9D%E5%AD%98%E5%8F%A5%E6%B3%95%E5%88%86%E6%9E%90%E8%AF%84%E4%BB%B7%E6%8C%87%E6%A0%87/
http://www.hankcs.com/nlp/parsing/crf-sequence-annotation-chinese-dependency-parser-implementation-based-on-java.html
http://universaldependencies.org/
http://www.hankcs.com/nlp/corpus/chinese-treebank.html#h3-6
https://github.com/tensorflow/models/blob/master/research/syntaxnet/g3doc/syntaxnet-tutorial.md
https://github.com/taolei87/RBGParser/wiki/Data-Format
There is now a CoNLL-U data format as well which extends the CoNLL-X format.
http://www.phontron.com/class/nn4nlp2018/schedule/transition-parsing.html https://www.youtube.com/watch?v=7rp2c7JVymE
This lecture (by Graham Neubig) for CMU CS 11-747, Neural Networks for NLP (Fall 2017) covers:
Slides: http://www.phontron.com/class/nn4nlp2018/schedule/transition-parsing.html Code Examples: https://github.com/neubig/nn4nlp-code
Previous Video: https://youtu.be/e5sPNlgbZAE Next Video: https://youtu.be/gRtEW6Q5XJE
See more details of the class here: http://phontron.com/class/nn4nlp2017/
https://wenku.baidu.com/view/b50dbedfe2bd960591c677d1.html
介绍句法分析
依存关系主要使用句法分析器完成,句法分析器也有基于规则的和基于机器学习训练的。 虽然实现方案不同,但是二者的模型输出的是同样一个规范: https://nlp.stanford.edu/software/lex-parser.shtml
目前,state of art的可以参考 http://nlp.qq.com/semantic.cgi 句法类API
Google SyntaxNet
SyntaxNet 中文模型的使用
https://my.oschina.net/dingdayu/blog/1083438
How to train Chinese corpus after downloading the universal-dependencies-2.0 ?
https://github.com/dsindex/syntaxnet/issues/24
Google自然语言理解工具syntaxnet开放中文支持
https://www.jianshu.com/p/479a111ed5f4
HanLP
生成式依存句法分析器的简单实现
http://www.hankcs.com/nlp/to-achieve-a-simple-generative-dependency-parsing.html
基于神经网络的高性能依存句法分析器
http://www.hankcs.com/nlp/parsing/neural-network-based-dependency-parser.html
dependency parsing
论文分析 https://www.zhihu.com/question/46272554 https://arxiv.org/pdf/1603.06042v1.pdf
开源项目
https://gist.github.com/Samurais/2c935182fb7213205284f7cd5040536a https://github.com/Xe0n0/python-dependency-parser
Greedy Transition-Based Parsing
http://demo.clab.cs.cmu.edu/fa2015-11711/images/b/b1/TbparsingSmallCorrection.pdf https://www.youtube.com/results?search_query=Greedy+Transition-Based+Parsing
依存句法分析评价指标
https://jiaxuncai.github.io/2016/10/30/%E4%BE%9D%E5%AD%98%E5%8F%A5%E6%B3%95%E5%88%86%E6%9E%90%E8%AF%84%E4%BB%B7%E6%8C%87%E6%A0%87/
基于CRF序列标注的中文依存句法分析器的Java实现
http://www.hankcs.com/nlp/parsing/crf-sequence-annotation-chinese-dependency-parser-implementation-based-on-java.html
用于训练的数据集
universaldependencies
http://universaldependencies.org/
采用清华大学语义依存网络语料的20000句作为训练集。
http://www.hankcs.com/nlp/corpus/chinese-treebank.html#h3-6
SyntaxNet Tutorial
https://github.com/tensorflow/models/blob/master/research/syntaxnet/g3doc/syntaxnet-tutorial.md
Conllu Data Format
https://github.com/taolei87/RBGParser/wiki/Data-Format
There is now a CoNLL-U data format as well which extends the CoNLL-X format.
CMU Neural Nets for NLP 2017 (12): Transition-based Dependency Parsing
http://www.phontron.com/class/nn4nlp2018/schedule/transition-parsing.html https://www.youtube.com/watch?v=7rp2c7JVymE
This lecture (by Graham Neubig) for CMU CS 11-747, Neural Networks for NLP (Fall 2017) covers:
Slides: http://www.phontron.com/class/nn4nlp2018/schedule/transition-parsing.html Code Examples: https://github.com/neubig/nn4nlp-code
Previous Video: https://youtu.be/e5sPNlgbZAE Next Video: https://youtu.be/gRtEW6Q5XJE
See more details of the class here: http://phontron.com/class/nn4nlp2017/