HOL-master/examples/lassie/sempre/src/edu/stanford/nlp/sempre/SimpleLexicon.java
package edu.stanford.nlp.sempre;

import fig.basic.*;

import java.io.BufferedReader;
import java.io.IOException;
import java.util.*;

import edu.stanford.nlp.sempre.interactive.lassie.HOLOntology;

/**
 * A Lexicon maps phrases (e.g., born) to lexical entries, which contain a
 * formula (e.g., fb:people.person.place_of_birth) and a type.
 * This class is meant to be simpler/faster than the normal
 * UnaryLexicon/BinaryLexicon.
 *
 * Note: this class exists because it was annoying to add types into the normal
 * UnaryLexicon and I didn't want to break backward compatibility with the rest
 * of the code.  Also, the normal lexicon is really slow with all those hash
 * maps.
 *
 * The lexicon here only knows about Formulas and fuzzy matching.
 * In the lexicon, we have rawPhrase.
 * In the user query, we have phrase.
 *
 * @author Percy Liang
 */
public final class SimpleLexicon {
  public static class Entry {
    // rawPhrase was the original phrase in the Lexicon
    public Entry(String rawPhrase, Formula formula, SemType type, StringDoubleVec features) {
      this.rawPhrase = rawPhrase;
      this.formula = formula;
      this.type = type;
      this.features = features;
    }
    public final String rawPhrase;
    public final Formula formula;
    public final SemType type;
    public final StringDoubleVec features;

    @Override public String toString() {
      return "[" + rawPhrase + " => " + formula + " : " + type + "]";
    }
  }

  public static class Options {
    @Option(gloss = "Path to load lexicon files from") public List<String> inPaths;
    @Option(gloss = "Types to allow suffix (last word) matche (for people names") public List<String> matchSuffixTypes;
    @Option(gloss = "Normalize lexicon phrases to lowercase") public boolean lowerCaseTokens = true;      
  }
  public static Options opts = new Options();

  private static SimpleLexicon lexicon;
  public static SimpleLexicon getSingleton() {
    if (lexicon == null) lexicon = new SimpleLexicon();
    return lexicon;
  }

  private SimpleLexicon() {
    if (opts.inPaths == null) return;
    HOLOntology.getTheOntology(); // make sure ontology (thus lexicon) was created
    for (String path : opts.inPaths) read(path);
  }

  // Mapping from phrase
  Map<String, List<Entry>> entries = new HashMap<String, List<Entry>>();

  public void read(String path) {
    LogInfo.begin_track("SimpleLexicon.read(%s)", path);
    try {
      BufferedReader in = IOUtils.openIn(path);
      String line;
      int numLines = 0;
      int oldNumEntries = entries.size();
      while ((line = in.readLine()) != null) {
        Map<String, Object> map = Json.readMapHard(line);
        numLines++;

        String rawPhrase = (String) map.get("lexeme");
        Formula formula = Formula.fromString((String) map.get("formula"));

        // Type
        String typeStr = (String) map.get("type");
        SemType type = typeStr != null ? SemType.fromString(typeStr) : TypeInference.inferType(formula);

        // Features
        StringDoubleVec features = null;
        Map<String, Double> featureMap = (Map<String, Double>) map.get("features");
        if (featureMap != null) {
          features = new StringDoubleVec();
          for (Map.Entry<String, Double> e : featureMap.entrySet())
            features.add(e.getKey(), e.getValue());
          features.trimToSize();
        }

        // Add verbatim feature
        Entry entry = new Entry(rawPhrase, formula, type, features);
	String phrase = rawPhrase;
	if (opts.lowerCaseTokens) {
	    phrase = entry.rawPhrase.toLowerCase();
	}
        MapUtils.addToList(entries, phrase, entry);

        // For last names
        String[] parts = phrase.split(" ");
        if (opts.matchSuffixTypes != null && opts.matchSuffixTypes.contains(typeStr) && parts.length > 1) {
          StringDoubleVec newFeatures = new StringDoubleVec();
          if (features != null) {  // Copy over features
            for (StringDoubleVec.Entry e : features)
              newFeatures.add(e.getFirst(), e.getSecond());
          }
          newFeatures.add("isSuffix", 1);
          newFeatures.trimToSize();
          Entry newEntry = new Entry(rawPhrase, formula, type, newFeatures);
          MapUtils.addToList(entries, parts[parts.length - 1], newEntry);
        }
        // In the future, add other mechanisms for lemmatization.
      }
      LogInfo.logs("Read %s lines, generated %d entries (now %d total)", numLines, entries.size() - oldNumEntries, entries.size());
    } catch (IOException e) {
      throw new RuntimeException(e);
    }
    LogInfo.end_track();
  }

  public List<Entry> lookup(String phrase) {
    return MapUtils.get(entries, phrase, Collections.EMPTY_LIST);
  }
}
