wordnet关系

Question

如何从wordnet中生成更一般的、更不一般的和等价的关系？

RitaWordnet中的wordnet相似度给出了一个类似于- 1.0，0.222或1.0的数字，但是如何得出单词之间更一般，更不一般的关系呢？哪种工具是最理想的呢？请帮帮我

我得到了java.lang.NullPointerException，在它打印出"the holonyms are“之后。

package wordnet;

import rita.wordnet.RiWordnet;

public class Main {
    public static void main(String[] args) {
        try {
            // Would pass in a PApplet normally, but we don't need to here
            RiWordnet wordnet = new RiWordnet();
            wordnet.setWordnetHome("/usr/share/wordnet/dict");
            // Demo finding parts of speech
            String word = "first name";
            System.out.println("\nFinding parts of speech for " + word + ".");
            String[] partsofspeech = wordnet.getPos(word);
            for (int i = 0; i < partsofspeech.length; i++) {
                System.out.println(partsofspeech[i]);
            }

            //word = "eat";
            String pos = wordnet.getBestPos(word);
            System.out.println("\n\nDefinitions for " + word + ":");
            // Get an array of glosses for a word
            String[] glosses = wordnet.getAllGlosses(word, pos);
            // Display all definitions
            for (int i = 0; i < glosses.length; i++) {
                System.out.println(glosses[i]);
            }

            // Demo finding a list of related words (synonyms)
            //word = "first name";
            String[] poss = wordnet.getPos(word);
            for (int j = 0; j < poss.length; j++) {
                System.out.println("\n\nSynonyms for " + word + " (pos: " + poss[j] + ")");
                String[] synonyms = wordnet.getAllSynonyms(word, poss[j], 10);
                for (int i = 0; i < synonyms.length; i++) {
                    System.out.println(synonyms[i]);
                }
            }

            // Demo finding a list of related words
            // X is Hypernym of Y if every Y is of type X
            // Hyponym is the inverse
            //word = "nurse";
            pos = wordnet.getBestPos(word);
            System.out.println("\n\nHyponyms for " + word + ":");
            String[] hyponyms = wordnet.getAllHyponyms(word, pos);
            //System.out.println(hyponyms.length);
            //if(hyponyms!=null)
            for (int i = 0; i < hyponyms.length; i++) {


                System.out.println(hyponyms[i]);
            }

            System.out.println("\n\nHypernyms for " + word + ":");
            String[] hypernyms = wordnet.getAllHypernyms(word, pos);
            //if(hypernyms!=null)
            for (int i = 0; i < hypernyms.length; i++) {
                System.out.println(hypernyms[i]);
            }

               System.out.println("\n\nHolonyms for " + word + ":");

            String[] holonyms = wordnet.getAllHolonyms(word, pos);
            //if(holonyms!=null)
            for (int i = 0; i < holonyms.length; i++) {
                System.out.println(holonyms[i]);
            }

              System.out.println("\n\nmeronyms for " + word + ":");
            String[] meronyms = wordnet.getAllMeronyms(word, pos);
            if(meronyms!=null)
            for (int i = 0; i < meronyms.length; i++) {
                System.out.println(meronyms[i]);
            }
              System.out.println("\n\nAntonym for " + word + ":");
            String[] antonyms = wordnet.getAllAntonyms(word, pos);
            if(antonyms!=null)
            for (int i = 0; i < antonyms.length; i++) {
                System.out.println(antonyms[i]);
            }


            String start = "cameras";
            String end = "digital cameras";
            pos = wordnet.getBestPos(start);

            // Wordnet can find relationships between words
            System.out.println("\n\nRelationship between: " + start + " and " + end);
            float dist = wordnet.getDistance(start, end, pos);
            String[] parents = wordnet.getCommonParents(start, end, pos);
            System.out.println(start + " and " + end + " are related by a distance of: " + dist);

            // These words have common parents (hyponyms in this case)
            System.out.println("Common parents: ");
            if (parents != null) {
                for (int i = 0; i < parents.length; i++) {
                    System.out.println(parents[i]);
                }
            }

            //wordnet.
            // System.out.println("\n\nHypernym Tree for " + start);
            // int[] ids = wordnet.getSenseIds(start,wordnet.NOUN);
            // wordnet.printHypernymTree(ids[0]);
        } catch (Exception e) {
            e.printStackTrace();
        }
     }
  }

Answer 1

Rita wordnet确实提供了用于查找上位词(更通用)、下位词(不太通用)和同义词的api。有关详情，请参阅以下网页：

http://www.rednoise.org/rita/wordnet/documentation/index.htm

要了解所有这些术语(超词等)，请查看wordnet的维基百科页面。

Answer 2

您可以尝试自己解析数据库。不会那么难的。1)在以下文件中找到单词: index.noun，index.verb，index.adj和index.noun，2)提取其同义词的id (“词义”)，对于每个同义词，转到data.noun，data.verb，data.adj或data.noun，并提取其上位词或下位词的同义词id。然后搜索这些同义词和注释的同义词ids。如果你使用正则表达式，这是相当容易的。

数据库(例如index.verb)可以在Wordnet的一个目录中找到，您可以从here下载该目录。如果您使用的是Linux，也有一个很好的命令行程序可以为您完成这项工作，但是如果您希望将其集成到Java代码中，恐怕您必须自己完成所有的解析工作。您可能还会发现this link很有趣。希望这能有所帮助：)

PS:你也可以试试NLTK (用Python语言编写)