如何在R中使用wordnet获取单词层次结构(例如，上位词，下位词) [英] How to get word hierarchy (e.g., hypernyms, hyponyms) using wordnet in R

问题描述

我想在R中使用wordnet软件包来获得单词层次结构，例如:动物"是猫"的上位词，苹果"是水果"的下位词.但是我可以从R wordnet帮助文件中找到的代码如下所示，用于识别反义词:

I want to use the wordnet package in R to get the word hierarchies like: "animal" is the hypernym of "cat", and "apple" is the hyponym of "fruit". But the code I can find from R wordnet help file is like below to identify antonyms:

install.packages("wordnet", dependencies=TRUE)
library(wordnet)
filter <- getTermFilter("ExactMatchFilter", "cold", TRUE)
terms <- getIndexTerms("ADJECTIVE", 5, filter)
synsets <- getSynsets(terms[[1]])
related <- getRelatedSynsets(synsets[[1]],"!")
sapply(related, getWord)

如何使用R wordnet程序包查找单词的上位词和下位词?

How can I use the R wordnet package to find hypernyms and hyponyms of a word?

推荐答案

您可以在

related <- getRelatedSynsets(synsets[[1]],"!")

根据需要使用其他符号.

with other symbols depending on what you need.

查看此链接: http://wordnet.princeton.edu/man/wnsearch.3WN.html# sect4

高位字母为"@"

原始问题的扩展名:

我刚刚开始使用WordNet，并且正在寻找类似的东西. 对于苹果"，我想要一棵高个的树给我

I just started using WordNet and I am looking for something similar. For 'apple' I would like a hypernym tree giving me

• '水果'
  • 食物"
    • 固体物质"
      • 物理实体"
        • 等...
        • 'fruit'
          • 'food'
            • 'solid matter'
              • 'physical entity'
                • etc...

                在WordNet在线上单击inherited hypernyms时可以看到 http://wordnetweb.princeton.edu/perl/webwn

                as can be seen when clicking on inherited hypernyms on WordNet online http://wordnetweb.princeton.edu/perl/webwn

                但是，以下命令

                filter <- getTermFilter(type="ExactMatchFilter", word="apple", ignoreCase=TRUE)
                terms <- getIndexTerms("NOUN", 15, filter)
                synsets <- getSynsets(terms[[1]])
                related <- getRelatedSynsets(synsets[[1]], "@")
                sapply(related, getWord)
                

                只会给我

                [[1]]
                [1] "edible fruit"
                
                [[2]]
                [1] "pome"        "false fruit"
                

                因此无法为我提供较低级别的上位词

                hence failing to provide me with lower levels of hypernyms

                爬上上级树的关键是递归使用getRelatedSynsets().

                继续上面的示例，从苹果的同义词集中提取同义词:

                Continuing with the above example, extracting synsets from apple's synsets:

                related_2 <- getRelatedSynsets(related[[1]], "@")
                

                并收集相应的单词:

                sapply(related_2, getWord)
                

                将产生:

                [[1]]
                [1] "produce"         "green goods"     "green groceries" "garden truck"   
                
                [[2]]
                [1] "fruit"
                

                并进一步:

                related_3 <- getRelatedSynsets(related2[[1]], "@")
                
                sapply(related_3, getWord)
                

                将导致:

                [,1]        
                [1,] "food"      
                [2,] "solid food"
                

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