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Stanford CoreNLP provides a set of natural language analysis tools which can take raw English language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and word dependencies, and indicate which noun phrases refer to the same entities. It provides the foundational building blocks for higher level text understanding applications.

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package edu.stanford.nlp.parser.lexparser;

import java.util.*;

import edu.stanford.nlp.util.Index;

public class OutsideRuleFilter {

  private final Index tagIndex;
  private int numTags;
  private int numFAs;

  protected FA[] leftFA;
  protected FA[] rightFA;

  protected static  List reverse(List list) {
    int sz = list.size();
    List reverse = new ArrayList<>(sz);
    for (int i = sz - 1; i >= 0; i--) {
      reverse.add(list.get(i));
    }
    return reverse;
  }

  protected FA buildFA(List tags) {
    FA fa = new FA(tags.size() + 1, numTags);
    fa.setLoopState(0, true);
    for (int state = 1; state <= tags.size(); state++) {
      String tagO = tags.get(state - 1);
      if (tagO == null) {
        fa.setLoopState(state, true);
        for (int symbol = 0; symbol < numTags; symbol++) {
          fa.setTransition(state - 1, symbol, state);
        }
      } else {
        int tag = tagIndex.indexOf(tagO);
        fa.setTransition(state - 1, tag, state);
      }
    }
    return fa;
  }

  protected final void registerRule(List leftTags, List rightTags, int state) {
    leftFA[state] = buildFA(leftTags);
    rightFA[state] = buildFA(reverse(rightTags));
  }

  public void init() {
    for (int rule = 0; rule < numFAs; rule++) {
      leftFA[rule].init();
      rightFA[rule].init();
    }
  }

  public void advanceRight(boolean[] tags) {
    for (int tag = 0; tag < numTags; tag++) {
      if (!tags[tag]) {
        continue;
      }
      for (int rule = 0; rule < numFAs; rule++) {
        leftFA[rule].input(tag);
      }
    }
    for (int rule = 0; rule < numFAs; rule++) {
      leftFA[rule].advance();
    }
  }

  public void leftAccepting(boolean[] result) {
    for (int rule = 0; rule < numFAs; rule++) {
      result[rule] = leftFA[rule].isAccepting();
    }
  }

  public void advanceLeft(boolean[] tags) {
    for (int tag = 0; tag < numTags; tag++) {
      if (!tags[tag]) {
        continue;
      }
      for (int rule = 0; rule < numFAs; rule++) {
        rightFA[rule].input(tag);
      }
    }
    for (int rule = 0; rule < numFAs; rule++) {
      rightFA[rule].advance();
    }
  }

  public void rightAccepting(boolean[] result) {
    for (int rule = 0; rule < numFAs; rule++) {
      result[rule] = rightFA[rule].isAccepting();
    }
  }

  private void allocate(int numFAs) {
    this.numFAs = numFAs;
    leftFA = new FA[numFAs];
    rightFA = new FA[numFAs];
  }

  public OutsideRuleFilter(BinaryGrammar bg, Index stateIndex, Index tagIndex) {
    this.tagIndex = tagIndex;
    int numStates = stateIndex.size();
    numTags = tagIndex.size();
    allocate(numStates);
    for (int state = 0; state < numStates; state++) {
      String stateStr = stateIndex.get(state);
      List left = new ArrayList<>();
      List right = new ArrayList<>();
      if (!bg.isSynthetic(state)) {
        registerRule(left, right, state);
        continue;
      }
      boolean foundSemi = false;
      boolean foundDots = false;
      List array = left;
      StringBuilder sb = new StringBuilder();
      for (int c = 0; c < stateStr.length(); c++) {
        if (stateStr.charAt(c) == ':') {
          foundSemi = true;
          continue;
        }
        if (!foundSemi) {
          continue;
        }
        if (stateStr.charAt(c) == ' ') {
          if (sb.length() > 0) {
            String str = sb.toString();
            if (!tagIndex.contains(str)) {
              str = null;
            }
            array.add(str);
            sb = new StringBuilder();
          }
          continue;
        }
        if (!foundDots && stateStr.charAt(c) == '.') {
          c += 3;
          foundDots = true;
          array = right;
          continue;
        }
        sb.append(stateStr.charAt(c));
      }
      registerRule(left, right, state);
    }
  }

  /** This is a simple Finite Automaton implementation. */
  static class FA {
    protected boolean[] inStatePrev;
    protected boolean[] inStateNext;
    protected boolean[] loopState;
    protected int acceptingState;
    protected int initialState;
    protected int numStates;
    protected int numSymbols;
    protected int[][] transition; // state x tag

    public void init() {
      Arrays.fill(inStatePrev, false);
      Arrays.fill(inStateNext, false);
      inStatePrev[initialState] = true;
    }

    public void input(int symbol) {
      for (int prevState = 0; prevState < numStates; prevState++) {
        if (inStatePrev[prevState]) {
          inStateNext[transition[prevState][symbol]] = true;
        }
      }
    }

    public void advance() {
      boolean[] temp = inStatePrev;
      inStatePrev = inStateNext;
      inStateNext = temp;
      Arrays.fill(inStateNext, false);
      for (int state = 0; state < numStates; state++) {
        if (inStatePrev[state] && loopState[state]) {
          inStateNext[state] = true;
        }
      }
    }

    public boolean isAccepting() {
      return inStatePrev[acceptingState];
    }

    public void setTransition(int state, int symbol, int result) {
      transition[state][symbol] = result;
    }

    public void setLoopState(int state, boolean loops) {
      loopState[state] = loops;
    }

    public FA(int numStates, int numSymbols) {
      this.numStates = numStates;
      this.numSymbols = numSymbols;
      acceptingState = numStates - 1;
      inStatePrev = new boolean[numStates];
      inStateNext = new boolean[numStates];
      loopState = new boolean[numStates];
      transition = new int[numStates][numSymbols];
    }

  } // end class FA
  
} // end class OutsideRuleFilter




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