opennlp.tools.parser.AbstractBottomUpParser Maven / Gradle / Ivy
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* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
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* See the License for the specific language governing permissions and
* limitations under the License.
*/
package opennlp.tools.parser;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import java.util.Set;
import java.util.SortedSet;
import java.util.TreeSet;
import opennlp.tools.chunker.Chunker;
import opennlp.tools.dictionary.Dictionary;
import opennlp.tools.ngram.NGramModel;
import opennlp.tools.parser.chunking.ParserEventStream;
import opennlp.tools.postag.POSTagger;
import opennlp.tools.util.ObjectStream;
import opennlp.tools.util.Sequence;
import opennlp.tools.util.Span;
import opennlp.tools.util.StringList;
import opennlp.tools.util.TrainingParameters;
/**
* Abstract class which contains code to tag and chunk parses for bottom up parsing and
* leaves implementation of advancing parses and completing parses to extend class.
*
* Note:
The nodes within the returned parses are shared with other parses
* and therefore their parent node references will not be consistent with their child
* node reference. {@link #setParents setParents} can be used to make the parents consistent
* with a particular parse, but subsequent calls to setParents can invalidate
* the results of earlier calls.
*/
public abstract class AbstractBottomUpParser implements Parser {
/**
* The maximum number of parses advanced from all preceding
* parses at each derivation step.
*/
protected int M;
/**
* The maximum number of parses to advance from a single preceding parse.
*/
protected int K;
/**
* The minimum total probability mass of advanced outcomes.
*/
protected double Q;
/**
* The default beam size used if no beam size is given.
*/
public static final int defaultBeamSize = 20;
/**
* The default amount of probability mass required of advanced outcomes.
*/
public static final double defaultAdvancePercentage = 0.95;
/**
* Completed parses.
*/
private SortedSet completeParses;
/**
* Incomplete parses which will be advanced.
*/
private SortedSet odh;
/**
* Incomplete parses which have been advanced.
*/
private SortedSet ndh;
/**
* The head rules for the parser.
*/
protected HeadRules headRules;
/**
* The set strings which are considered punctuation for the parser.
* Punctuation is not attached, but floats to the top of the parse as attachment
* decisions are made about its non-punctuation sister nodes.
*/
protected Set punctSet;
/**
* The label for the top node.
*/
public static final String TOP_NODE = "TOP";
/**
* The label for the top if an incomplete node.
*/
public static final String INC_NODE = "INC";
/**
* The label for a token node.
*/
public static final String TOK_NODE = "TK";
/**
* The integer 0.
*/
public static final Integer ZERO = 0;
/**
* Prefix for outcomes starting a constituent.
*/
public static final String START = "S-";
/**
* Prefix for outcomes continuing a constituent.
*/
public static final String CONT = "C-";
/**
* Outcome for token which is not contained in a basal constituent.
*/
public static final String OTHER = "O";
/**
* Outcome used when a constituent is complete.
*/
public static final String COMPLETE = "c";
/**
* Outcome used when a constituent is incomplete.
*/
public static final String INCOMPLETE = "i";
/**
* The pos-tagger that the parser uses.
*/
protected POSTagger tagger;
/**
* The chunker that the parser uses to chunk non-recursive structures.
*/
protected Chunker chunker;
/**
* Specifies whether failed parses should be reported to standard error.
*/
protected boolean reportFailedParse;
/**
* Specifies whether a derivation string should be created during parsing.
* This is useful for debugging.
*/
protected boolean createDerivationString = false;
/**
* Turns debug print on or off.
*/
protected boolean debugOn = false;
public AbstractBottomUpParser(POSTagger tagger, Chunker chunker, HeadRules headRules,
int beamSize, double advancePercentage) {
this.tagger = tagger;
this.chunker = chunker;
this.M = beamSize;
this.K = beamSize;
this.Q = advancePercentage;
reportFailedParse = true;
this.headRules = headRules;
this.punctSet = headRules.getPunctuationTags();
odh = new TreeSet<>();
ndh = new TreeSet<>();
completeParses = new TreeSet<>();
}
/**
* Specifies whether the parser should report when it was unable to find a parse for
* a particular sentence.
* @param errorReporting If true then un-parsed sentences are reported, false otherwise.
*/
public void setErrorReporting(boolean errorReporting) {
this.reportFailedParse = errorReporting;
}
/**
* Assigns parent references for the specified parse so that they
* are consistent with the children references.
* @param p The parse whose parent references need to be assigned.
*/
public static void setParents(Parse p) {
Parse[] children = p.getChildren();
for (int ci = 0; ci < children.length; ci++) {
children[ci].setParent(p);
setParents(children[ci]);
}
}
/**
* Removes the punctuation from the specified set of chunks, adds it to the parses
* adjacent to the punctuation is specified, and returns a new array of parses with
* the punctuation removed.
*
* @param chunks A set of parses.
* @param punctSet The set of punctuation which is to be removed.
* @return An array of parses which is a subset of chunks with punctuation removed.
*/
public static Parse[] collapsePunctuation(Parse[] chunks, Set punctSet) {
List collapsedParses = new ArrayList<>(chunks.length);
int lastNonPunct = -1;
int nextNonPunct;
for (int ci = 0, cn = chunks.length; ci < cn; ci++) {
if (punctSet.contains(chunks[ci].getType())) {
if (lastNonPunct >= 0) {
chunks[lastNonPunct].addNextPunctuation(chunks[ci]);
}
for (nextNonPunct = ci + 1; nextNonPunct < cn; nextNonPunct++) {
if (!punctSet.contains(chunks[nextNonPunct].getType())) {
break;
}
}
if (nextNonPunct < cn) {
chunks[nextNonPunct].addPreviousPunctuation(chunks[ci]);
}
}
else {
collapsedParses.add(chunks[ci]);
lastNonPunct = ci;
}
}
if (collapsedParses.size() == chunks.length) {
return chunks;
}
//System.err.println("collapsedPunctuation: collapsedParses"+collapsedParses);
return collapsedParses.toArray(new Parse[collapsedParses.size()]);
}
/**
* Advances the specified parse and returns the an array advanced parses whose
* probability accounts for more than the specified amount of probability mass.
*
* @param p The parse to advance.
* @param probMass The amount of probability mass that should be accounted for
* by the advanced parses.
*/
protected abstract Parse[] advanceParses(final Parse p, double probMass);
/**
* Adds the "TOP" node to the specified parse.
* @param p The complete parse.
*/
protected abstract void advanceTop(Parse p);
public Parse[] parse(Parse tokens, int numParses) {
if (createDerivationString) tokens.setDerivation(new StringBuffer(100));
odh.clear();
ndh.clear();
completeParses.clear();
int derivationStage = 0; //derivation length
int maxDerivationLength = 2 * tokens.getChildCount() + 3;
odh.add(tokens);
Parse guess = null;
double minComplete = 2;
double bestComplete = -100000; //approximating -infinity/0 in ln domain
while (odh.size() > 0 && (completeParses.size() < M || (odh.first()).getProb() < minComplete)
&& derivationStage < maxDerivationLength) {
ndh = new TreeSet<>();
int derivationRank = 0;
for (Iterator pi = odh.iterator(); pi.hasNext()
&& derivationRank < K; derivationRank++) { // foreach derivation
Parse tp = pi.next();
//TODO: Need to look at this for K-best parsing cases
/*
//this parse and the ones which follow will never win, stop advancing.
if (tp.getProb() < bestComplete) {
break;
}
*/
if (guess == null && derivationStage == 2) {
guess = tp;
}
if (debugOn) {
System.out.print(derivationStage + " " + derivationRank + " " + tp.getProb());
tp.show();
System.out.println();
}
Parse[] nd;
if (0 == derivationStage) {
nd = advanceTags(tp);
}
else if (1 == derivationStage) {
if (ndh.size() < K) {
//System.err.println("advancing ts "+j+" "+ndh.size()+" < "+K);
nd = advanceChunks(tp,bestComplete);
}
else {
//System.err.println("advancing ts "+j+" prob="+((Parse) ndh.last()).getProb());
nd = advanceChunks(tp,(ndh.last()).getProb());
}
}
else { // i > 1
nd = advanceParses(tp, Q);
}
if (nd != null) {
for (int k = 0, kl = nd.length; k < kl; k++) {
if (nd[k].complete()) {
advanceTop(nd[k]);
if (nd[k].getProb() > bestComplete) {
bestComplete = nd[k].getProb();
}
if (nd[k].getProb() < minComplete) {
minComplete = nd[k].getProb();
}
completeParses.add(nd[k]);
}
else {
ndh.add(nd[k]);
}
}
}
else {
//if (reportFailedParse) {
// System.err.println("Couldn't advance parse " + derivationStage
// + " stage " + derivationRank + "!\n");
//}
advanceTop(tp);
completeParses.add(tp);
}
}
derivationStage++;
odh = ndh;
}
if (completeParses.size() == 0) {
// if (reportFailedParse) System.err.println("Couldn't find parse for: " + tokens);
//Parse r = (Parse) odh.first();
//r.show();
//System.out.println();
return new Parse[] {guess};
}
else if (numParses == 1) {
return new Parse[] {completeParses.first()};
}
else {
List topParses = new ArrayList<>(numParses);
while (!completeParses.isEmpty() && topParses.size() < numParses) {
Parse tp = completeParses.last();
completeParses.remove(tp);
topParses.add(tp);
//parses.remove(tp);
}
return topParses.toArray(new Parse[topParses.size()]);
}
}
public Parse parse(Parse tokens) {
if (tokens.getChildCount() > 0) {
Parse p = parse(tokens,1)[0];
setParents(p);
return p;
}
else {
return tokens;
}
}
/**
* Returns the top chunk sequences for the specified parse.
* @param p A pos-tag assigned parse.
* @param minChunkScore A minimum score below which chunks should not be advanced.
* @return The top chunk assignments to the specified parse.
*/
protected Parse[] advanceChunks(final Parse p, double minChunkScore) {
// chunk
Parse[] children = p.getChildren();
String[] words = new String[children.length];
String[] ptags = new String[words.length];
double[] probs = new double[words.length];
for (int i = 0, il = children.length; i < il; i++) {
Parse sp = children[i];
words[i] = sp.getHead().getCoveredText();
ptags[i] = sp.getType();
}
//System.err.println("adjusted mcs = "+(minChunkScore-p.getProb()));
Sequence[] cs = chunker.topKSequences(words, ptags,minChunkScore - p.getProb());
Parse[] newParses = new Parse[cs.length];
for (int si = 0, sl = cs.length; si < sl; si++) {
newParses[si] = (Parse) p.clone(); //copies top level
if (createDerivationString) newParses[si].getDerivation().append(si).append(".");
String[] tags = cs[si].getOutcomes().toArray(new String[words.length]);
cs[si].getProbs(probs);
int start = -1;
int end = 0;
String type = null;
//System.err.print("sequence "+si+" ");
for (int j = 0; j <= tags.length; j++) {
// if (j != tags.length) {System.err.println(words[j]+" "
// +ptags[j]+" "+tags[j]+" "+probs.get(j));}
if (j != tags.length) {
newParses[si].addProb(StrictMath.log(probs[j]));
}
// if continue just update end chunking tag don't use contTypeMap
if (j != tags.length && tags[j].startsWith(CONT)) {
end = j;
}
else { //make previous constituent if it exists
if (type != null) {
//System.err.println("inserting tag "+tags[j]);
Parse p1 = p.getChildren()[start];
Parse p2 = p.getChildren()[end];
// System.err.println("Putting "+type+" at "+start+","+end+" for "
// +j+" "+newParses[si].getProb());
Parse[] cons = new Parse[end - start + 1];
cons[0] = p1;
//cons[0].label="Start-"+type;
if (end - start != 0) {
cons[end - start] = p2;
//cons[end-start].label="Cont-"+type;
for (int ci = 1; ci < end - start; ci++) {
cons[ci] = p.getChildren()[ci + start];
//cons[ci].label="Cont-"+type;
}
}
Parse chunk = new Parse(p1.getText(), new Span(p1.getSpan().getStart(),
p2.getSpan().getEnd()), type, 1, headRules.getHead(cons, type));
chunk.isChunk(true);
newParses[si].insert(chunk);
}
if (j != tags.length) { //update for new constituent
if (tags[j].startsWith(START)) { // don't use startTypeMap these are chunk tags
type = tags[j].substring(START.length());
start = j;
end = j;
}
else { // other
type = null;
}
}
}
}
//newParses[si].show();System.out.println();
}
return newParses;
}
/**
* Advances the parse by assigning it POS tags and returns multiple tag sequences.
* @param p The parse to be tagged.
* @return Parses with different POS-tag sequence assignments.
*/
protected Parse[] advanceTags(final Parse p) {
Parse[] children = p.getChildren();
String[] words = new String[children.length];
double[] probs = new double[words.length];
for (int i = 0,il = children.length; i < il; i++) {
words[i] = children[i].getCoveredText();
}
Sequence[] ts = tagger.topKSequences(words);
Parse[] newParses = new Parse[ts.length];
for (int i = 0; i < ts.length; i++) {
String[] tags = ts[i].getOutcomes().toArray(new String[words.length]);
ts[i].getProbs(probs);
newParses[i] = (Parse) p.clone(); //copies top level
if (createDerivationString) newParses[i].getDerivation().append(i).append(".");
for (int j = 0; j < words.length; j++) {
Parse word = children[j];
//System.err.println("inserting tag "+tags[j]);
double prob = probs[j];
newParses[i].insert(new Parse(word.getText(), word.getSpan(), tags[j], prob,j));
newParses[i].addProb(StrictMath.log(prob));
}
}
return newParses;
}
/**
* Determines the mapping between the specified index into the specified parses without punctuation to
* the corresponding index into the specified parses.
* @param index An index into the parses without punctuation.
* @param nonPunctParses The parses without punctuation.
* @param parses The parses wit punctuation.
* @return An index into the specified parses which corresponds to the same node the specified index
* into the parses with punctuation.
*/
protected int mapParseIndex(int index, Parse[] nonPunctParses, Parse[] parses) {
int parseIndex = index;
while (parses[parseIndex] != nonPunctParses[index]) {
parseIndex++;
}
return parseIndex;
}
private static boolean lastChild(Parse child, Parse parent, Set punctSet) {
if (parent == null) {
return false;
}
Parse[] kids = collapsePunctuation(parent.getChildren(), punctSet);
return (kids[kids.length - 1] == child);
}
/**
* Creates a n-gram dictionary from the specified data stream using the specified
* head rule and specified cut-off.
*
* @param data The data stream of parses.
* @param rules The head rules for the parses.
* @param params can contain a cutoff, the minimum number of entries required for the
* n-gram to be saved as part of the dictionary.
* @return A dictionary object.
*/
public static Dictionary buildDictionary(ObjectStream data, HeadRules rules,
TrainingParameters params) throws IOException {
int cutoff = params.getIntParameter("dict", TrainingParameters.CUTOFF_PARAM, 5);
NGramModel mdict = new NGramModel();
Parse p;
while ((p = data.read()) != null) {
p.updateHeads(rules);
Parse[] pwords = p.getTagNodes();
String[] words = new String[pwords.length];
//add all uni-grams
for (int wi = 0;wi < words.length; wi++) {
words[wi] = pwords[wi].getCoveredText();
}
mdict.add(new StringList(words), 1, 1);
//add tri-grams and bi-grams for inital sequence
Parse[] chunks = collapsePunctuation(ParserEventStream.getInitialChunks(p),
rules.getPunctuationTags());
String[] cwords = new String[chunks.length];
for (int wi = 0; wi < cwords.length; wi++) {
cwords[wi] = chunks[wi].getHead().getCoveredText();
}
mdict.add(new StringList(cwords), 2, 3);
//emulate reductions to produce additional n-grams
int ci = 0;
while (ci < chunks.length) {
// System.err.println("chunks["+ci+"]="+chunks[ci].getHead().getCoveredText()
// +" chunks.length="+chunks.length + " " + chunks[ci].getParent());
if (chunks[ci].getParent() == null) {
chunks[ci].show();
}
if (lastChild(chunks[ci], chunks[ci].getParent(),rules.getPunctuationTags())) {
//perform reduce
int reduceStart = ci;
while (reduceStart >= 0 && chunks[reduceStart].getParent() == chunks[ci].getParent()) {
reduceStart--;
}
reduceStart++;
chunks = ParserEventStream.reduceChunks(chunks,ci,chunks[ci].getParent());
ci = reduceStart;
if (chunks.length != 0) {
String[] window = new String[5];
int wi = 0;
if (ci - 2 >= 0) window[wi++] = chunks[ci - 2].getHead().getCoveredText();
if (ci - 1 >= 0) window[wi++] = chunks[ci - 1].getHead().getCoveredText();
window[wi++] = chunks[ci].getHead().getCoveredText();
if (ci + 1 < chunks.length) window[wi++] = chunks[ci + 1].getHead().getCoveredText();
if (ci + 2 < chunks.length) window[wi++] = chunks[ci + 2].getHead().getCoveredText();
if (wi < 5) {
String[] subWindow = new String[wi];
System.arraycopy(window, 0, subWindow, 0, wi);
window = subWindow;
}
if (window.length >= 3) {
mdict.add(new StringList(window), 2, 3);
}
else if (window.length == 2) {
mdict.add(new StringList(window), 2, 2);
}
}
ci = reduceStart - 1; //ci will be incremented at end of loop
}
ci++;
}
}
//System.err.println("gas,and="+mdict.getCount((new TokenList(new String[] {"gas","and"}))));
mdict.cutoff(cutoff, Integer.MAX_VALUE);
return mdict.toDictionary(true);
}
/**
* Creates a n-gram dictionary from the specified data stream using the specified
* head rule and specified cut-off.
*
* @param data The data stream of parses.
* @param rules The head rules for the parses.
* @param cutoff The minimum number of entries required for the n-gram to be
* saved as part of the dictionary.
* @return A dictionary object.
*/
public static Dictionary buildDictionary(ObjectStream data, HeadRules rules, int cutoff)
throws IOException {
TrainingParameters params = new TrainingParameters();
params.put("dict", TrainingParameters.CUTOFF_PARAM, cutoff);
return buildDictionary(data, rules, params);
}
}