R- NLP -提取对
R- NLP -提取对
提问于 2021-11-18 23:05:35
- 嗨，伙计们，我刚开始使用R.的NLP算法，我想从pdf中提取一对(动词-名词)吗？我被一个频率的单词主题卡住了。比如“在刑事诉讼、民事诉讼和其他法律诉讼中代表客户，起草法律文件，或管理或为客户提供法律交易方面的建议。可能专攻某一领域，也可能在许多法律领域广泛应用。”
- I希望从中提取动词-名词。我会怎么做？
回答 1
Stack Overflow用户
发布于 2021-11-19 08:56:49
> library(udpipe)
> docs <- "Represent clients in criminal and civil litigation and other legal proceedings, draw up legal documents, or manage or advise clients on legal transactions. May specialize in a single area or may practice broadly in many areas of law."
> docs <- setNames(docs, "doc1")
> anno <- udpipe(docs, object = "english", udpipe_model_repo = "bnosac/udpipe.models.ud")
> anno <- cbind_dependencies(anno, type = "parent")
> subset(anno, upos_parent %in% c("NOUN", "VERB") & upos %in% c("NOUN", "VERB"),
+ select = c("doc_id", "paragraph_id", "sentence_id", "token", "token_parent", "dep_rel", "upos", "upos_parent"))
doc_id paragraph_id sentence_id token token_parent dep_rel upos upos_parent
2 doc1 1 1 clients Represent obj NOUN VERB
7 doc1 1 1 litigation Represent obl NOUN VERB
11 doc1 1 1 proceedings litigation conj NOUN NOUN
13 doc1 1 1 draw Represent conj VERB VERB
16 doc1 1 1 documents draw obj NOUN VERB
19 doc1 1 1 manage documents conj NOUN NOUN
21 doc1 1 1 advise clients conj NOUN NOUN
22 doc1 1 1 clients Represent obj NOUN VERB
25 doc1 1 1 transactions clients nmod NOUN NOUN
32 doc1 1 2 area specialize obl NOUN VERB
35 doc1 1 2 practice specialize conj VERB VERB
39 doc1 1 2 areas practice obl NOUN VERB
41 doc1 1 2 law areas nmod NOUN NOUN页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/70027860
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