org.wikibrain.sr.milnewitten.MilneWittenDisambiguator Maven / Gradle / Ivy
package org.wikibrain.sr.milnewitten;
import com.google.common.collect.Maps;
import com.typesafe.config.Config;
import com.typesafe.config.ConfigValueFactory;
import org.apache.commons.collections.CollectionUtils;
import org.wikibrain.conf.Configuration;
import org.wikibrain.conf.ConfigurationException;
import org.wikibrain.conf.Configurator;
import org.wikibrain.core.dao.DaoException;
import org.wikibrain.core.dao.DaoFilter;
import org.wikibrain.core.dao.LocalPageDao;
import org.wikibrain.core.lang.Language;
import org.wikibrain.core.lang.LocalId;
import org.wikibrain.core.lang.LocalString;
import org.wikibrain.core.model.NameSpace;
import org.wikibrain.phrases.PhraseAnalyzer;
import org.wikibrain.sr.SRMetric;
import org.wikibrain.sr.disambig.Disambiguator;
import org.wikibrain.utils.WbMathUtils;
import org.wikibrain.utils.WpCollectionUtils;
import java.util.*;
/**
* @author Shilad Sen
*
* A literal implementation of the disambiguator described in
* http://www.aaai.org/Papers/Workshops/2008/WS-08-15/WS08-15-005.pdf
*
* This is naively extended to support multiple strings and contexts.
*/
public class MilneWittenDisambiguator extends Disambiguator {
private final Language language;
private final LocalPageDao pageDao;
private final PhraseAnalyzer analyzer;
private final SRMetric metric;
private final int numPages;
/**
* Construct a new disambiguator that uses a particular metric.
*
* @param pageDao
* @param analyzer
* @param metric
* @throws DaoException
*/
public MilneWittenDisambiguator(LocalPageDao pageDao, PhraseAnalyzer analyzer, SRMetric metric) throws DaoException {
this.language = metric.getLanguage();
this.pageDao = pageDao;
this.analyzer = analyzer;
this.metric = metric;
this.numPages = pageDao.getCount(
new DaoFilter().setLanguages(language)
.setNameSpaces(NameSpace.ARTICLE)
.setRedirect(false)
.setDisambig(false));
}
/**
* Given
* @param phrases The target phrases being disambiguated.
* @param context Other phrases (in the same language as the target phrase)
* related to the target phrase being disambiguated that may
* aid disambiguation.
* @return
* @throws DaoException
*/
@Override
public List> disambiguate(List phrases, Set context) throws DaoException {
// Collect all phrases
List allPhrases = new ArrayList(
(context == null) ? phrases : CollectionUtils.union(phrases, context));
// Step 1: calculate most frequent candidate senses for each phrase
Map> candidates = Maps.newHashMap();
for (LocalString s : allPhrases) {
if (!s.getLanguage().equals(language)) {
throw new IllegalArgumentException("Disambiguator only supports language " + language);
}
candidates.put(s, analyzer.resolve(s.getLanguage(), s.getString(), 100));
}
// Step 1.5: Build mapping from local id to phrases that are candidates
Map> idsToPhrases = new HashMap>();
for (LocalString s : candidates.keySet()) {
for (LocalId lid : candidates.get(s).keySet()) {
if (!idsToPhrases.containsKey(lid)) {
idsToPhrases.put(lid, new HashSet());
}
idsToPhrases.get(lid).add(s);
}
}
// Step 2: calculate the sum of cosimilarities for each page
Map pageSims = getCosimilaritySums(candidates);
// Step 3: Choose the best options for each phrase
List> result = new ArrayList>();
for (LocalString p : phrases) {
result.add(
disambiguateOnePhrase(p, candidates.get(p), idsToPhrases, pageSims));
}
return result;
}
private LinkedHashMap disambiguateOnePhrase(LocalString phrase, LinkedHashMap candidates, Map> idsToPhrases, Map pageSims) throws DaoException {
// Identify the highest similarity for each page
float maxSimilarity = Float.NEGATIVE_INFINITY;
for (LocalId lid : candidates.keySet()) {
maxSimilarity = Math.max(maxSimilarity, pageSims.get(lid));
}
// Identify the most popular senses within 40% of the top similarity
Map scores = new HashMap();
double scoreSum = 0.0;
for (LocalId lid : candidates.keySet()) {
double sim = pageSims.get(lid);
if (sim < 0.4 * maxSimilarity) {
continue;
}
double pop = candidates.get(lid);
double phraseBonus = 0.0;
/*
TODO: figure out phraseBonus for multiple phrases
int numPhrases = 0;
int sumCounts = 0;
for (LocalString ls2 : idsToPhrases.get(lid)) {
numPhrases++;
sumCounts += getPhraseCount(phrase.getString() + " " + ls2.getString());
sumCounts += getPhraseCount(ls2.getString() + " " + phrase.getString());
}
if (sumCounts > 0) {
int maxExpectedValue = numPhrases * numPages / 50;
phraseBonus = Math.log(sumCounts + 1) / Math.log(maxExpectedValue);
phraseBonus = Math.min(0.5, phraseBonus);
}
System.err.println("phrase bonus for " + phrase + ", " + idsToPhrases.get(lid) + " is " + phraseBonus);
*/
double score = pop + phraseBonus;
scores.put(lid, (float) score);
scoreSum += score;
}
LinkedHashMap pageResult = new LinkedHashMap();
for (LocalId key : WpCollectionUtils.sortMapKeys(scores, true)) {
pageResult.put(key, (float) (scores.get(key) / scoreSum));
}
return pageResult;
}
/*
private int getPhraseCount(String phrase) throws DaoException {
PrunedCounts pages = analyzer.getDao().getPhraseCounts(language, phrase, 1);
if (pages == null) {
return 0;
} else {
return pages.getTotal();
}
}
*/
/**
* Return the sum of cosimilarity scores for all unique pages among the candidates.
* @param candidates
* @return
* @throws DaoException
*/
private Map getCosimilaritySums(Map> candidates) throws DaoException {
// Step 1: compute the page cosimilarity matrix
Set uniques = new HashSet();
for (LinkedHashMap prob : candidates.values()) {
uniques.addAll(prob.keySet());
}
List pages = new ArrayList(uniques);
double[][] cosim;
if (pages.isEmpty()){
cosim = new double[0][0];
} else {
int[] pageIds = new int[pages.size()];
for (int i=0; i pageSims = new HashMap();
for (int i = 0; i < pages.size(); i++) {
double sum = 0.0;
for (int j = 0; j < pages.size(); j++) {
if (i != j && WbMathUtils.isReal(cosim[i][j])) {
sum += Math.max(0, cosim[i][j]); // Hack: no negative numbers
}
}
// add 0.0001 to give every candidate a tiny chance and avoid divide by zero errors when there are no good options
pageSims.put(pages.get(i), (float)(sum + 0.0001));
}
return pageSims;
}
public static class Provider extends org.wikibrain.conf.Provider{
public Provider(Configurator configurator, Configuration config) throws ConfigurationException {
super(configurator,config);
}
@Override
public Class getType(){
return Disambiguator.class;
}
@Override
public String getPath(){
return "sr.disambig";
}
@Override
public Disambiguator get(String name, Config config, Map runtimeParams) throws ConfigurationException{
if (!config.getString("type").equals("milnewitten")){
return null;
}
if (runtimeParams == null || !runtimeParams.containsKey("language")){
throw new IllegalArgumentException("SimpleMilneWitten requires 'language' runtime parameter.");
}
Language lang = Language.getByLangCode(runtimeParams.get("language"));
PhraseAnalyzer pa = getConfigurator().get(PhraseAnalyzer.class, config.getString("phraseAnalyzer"));
LocalPageDao pageDao = getConfigurator().get(LocalPageDao.class);
// Create override config for sr metric and load it.
String srName = config.getString("metric");
Config newConfig = getConfig().get().getConfig("sr.metric.local." + srName)
.withValue("disambiguator", ConfigValueFactory.fromAnyRef("topResult"));
Map srRuntimeParams = new HashMap();
srRuntimeParams.put("language", lang.getLangCode());
SRMetric sr = getConfigurator().construct(SRMetric.class, srName, newConfig, srRuntimeParams);
try {
return new MilneWittenDisambiguator(pageDao, pa, sr);
} catch (DaoException e) {
throw new ConfigurationException(e);
}
}
}
}
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