SelectFn.java

package edu.stanford.nlp.sempre;

import fig.basic.LispTree;
import fig.basic.LogInfo;
import fig.basic.Option;

import java.util.List;

/**
 * Given a particular position i, return the ith element on the RHS of the
 * derivation's rule.
 *
 * @author Andrew Chou
 */
public class SelectFn extends SemanticFn {
  public static class Options {
    @Option(gloss = "Verbose") public int verbose = 0;
  }

  public static Options opts = new Options();

  // Which child derivation to select and return.
  int position = -1;

  public SelectFn() { }

  public SelectFn(int position) {
    init(LispTree.proto.newList("SelectFn", position + ""));
  }

  public void init(LispTree tree) {
    super.init(tree);
    this.position = Integer.valueOf(tree.child(1).value);
  }

  public DerivationStream call(final Example ex, final Callable c) {
    return new SingleDerivationStream() {
      @Override
      public Derivation createDerivation() {
        FeatureVector features = new FeatureVector();
        // TODO(pliang): move into FeatureExtractor
        if (FeatureExtractor.containsDomain("skipPos")) {
          for (int i = 0; i < c.getChildren().size(); ++i) {
            if (i != position) {
              Derivation child = c.child(i);
              for (int index = child.start; index < child.end; ++index) {
                List<String> posTags = ex.languageInfo.posTags;
                features.add("skipPos", posTags.get(index));
                if (opts.verbose > 0) {
                  LogInfo.logs(
                          "SelectFn: adding pos-skipping feature, pos: %s, word: %s",
                          posTags.get(index), ex.languageInfo.tokens.get(index));
                }
              }
            }
          }
        }
        return new Derivation.Builder()
                .withCallable(c)
                .withFormulaFrom(c.child(position))
                .localFeatureVector(features)
                .createDerivation();
      }
    };
  }
}