wordnet から、より一般的で一般的でない同値関係を生成する方法は?
RitaWordnet の wordnet の類似度は、-1.0、0.222、または 1.0 のような数値を示しますが、単語間のより一般的で一般的ではない関係に到達するにはどうすればよいでしょうか? そのためにどのツールが理想的でしょうか？私を助けてください
「ホロニムは」を出力した後、java.lang.NullPointerExceptionを取得します
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();
}
}
}