public static IList <Tree> GetTopParsesForOneTree(LexicalizedParser parser, int dvKBest, Tree tree, ITreeTransformer transformer)
{
IParserQuery pq = parser.ParserQuery();
IList <Word> sentence = tree.YieldWords();
// Since the trees are binarized and otherwise manipulated, we
// need to chop off the last word in order to remove the end of
// sentence symbol
if (sentence.Count <= 1)
{
return(null);
}
sentence = sentence.SubList(0, sentence.Count - 1);
if (!pq.Parse(sentence))
{
log.Info("Failed to use the given parser to reparse sentence \"" + sentence + "\"");
return(null);
}
IList <Tree> parses = new List <Tree>();
IList <ScoredObject <Tree> > bestKParses = pq.GetKBestPCFGParses(dvKBest);
foreach (ScoredObject <Tree> so in bestKParses)
{
Tree result = so.Object();
if (transformer != null)
{
result = transformer.TransformTree(result);
}
parses.Add(result);
}
return(parses);
}
private IList <Tree> DoOneSentence(IList <ParserConstraint> constraints, IList <CoreLabel> words)
{
IParserQuery pq = parser.ParserQuery();
pq.SetConstraints(constraints);
pq.Parse(words);
IList <Tree> trees = Generics.NewLinkedList();
try
{
// Use bestParse if kBest is set to 1.
if (this.kBest == 1)
{
Tree t = pq.GetBestParse();
if (t == null)
{
log.Warn("Parsing of sentence failed. " + "Will ignore and continue: " + SentenceUtils.ListToString(words));
}
else
{
double score = pq.GetBestScore();
t.SetScore(score % -10000.0);
trees.Add(t);
}
}
else
{
IList <ScoredObject <Tree> > scoredObjects = pq.GetKBestParses(this.kBest);
if (scoredObjects == null || scoredObjects.Count < 1)
{
log.Warn("Parsing of sentence failed. " + "Will ignore and continue: " + SentenceUtils.ListToString(words));
}
else
{
foreach (ScoredObject <Tree> so in scoredObjects)
{
// -10000 denotes unknown words
Tree tree = so.Object();
tree.SetScore(so.Score() % -10000.0);
trees.Add(tree);
}
}
}
}
catch (OutOfMemoryException e)
{
log.Error(e);
// Beware that we can now get an OOM in logging, too.
log.Warn("Parsing of sentence ran out of memory (length=" + words.Count + "). " + "Will ignore and try to continue.");
}
catch (NoSuchParseException)
{
log.Warn("Parsing of sentence failed, possibly because of out of memory. " + "Will ignore and continue: " + SentenceUtils.ListToString(words));
}
return(trees);
}
public virtual IParserQuery Process <_T0>(IList <_T0> sentence)
where _T0 : IHasWord
{
IParserQuery pq = pqFactory.ParserQuery();
if (pwErr != null)
{
pq.ParseAndReport(sentence, pwErr);
}
else
{
pq.Parse(sentence);
}
return(pq);
}
public virtual bool Parse <_T0>(IList <_T0> sentence)
where _T0 : IHasWord
{
bool success = parserQuery.Parse(sentence);
if (!success)
{
return(false);
}
IList <ScoredObject <Tree> > bestKParses = parserQuery.GetKBestPCFGParses(rerankerKBest);
if (bestKParses.IsEmpty())
{
return(false);
}
scoredTrees = Rerank(sentence, bestKParses);
return(true);
}
public override void Run()
{
bool successful;
IParserQuery parserQuery = this._enclosing.parser.ParserQuery();
try
{
successful = parserQuery.Parse(this.sentence);
}
catch (Exception)
{
this._enclosing.StopProgressMonitor();
JOptionPane.ShowMessageDialog(this._enclosing, "Could not parse selected sentence\n(sentence probably too long)", null, JOptionPane.ErrorMessage);
this._enclosing.SetStatus("Error parsing");
return;
}
this._enclosing.StopProgressMonitor();
this._enclosing.SetStatus("Done");
if (successful)
{
// display the best parse
Tree tree = parserQuery.GetBestParse();
//tree.pennPrint();
this._enclosing.treePanel.SetTree(tree);
this._enclosing.clearButton.SetEnabled(true);
}
else
{
JOptionPane.ShowMessageDialog(this._enclosing, "Could not parse selected sentence", null, JOptionPane.ErrorMessage);
this._enclosing.SetStatus("Error parsing");
this._enclosing.treePanel.SetTree(null);
this._enclosing.clearButton.SetEnabled(false);
}
if (this._enclosing.scrollWhenDone)
{
this._enclosing.ScrollForward();
}
}
/// <exception cref="System.Exception"/>
public static void Main(string[] args)
{
string modelPath = null;
string outputPath = null;
string testTreebankPath = null;
IFileFilter testTreebankFilter = null;
IList <string> unusedArgs = new List <string>();
for (int argIndex = 0; argIndex < args.Length;)
{
if (Sharpen.Runtime.EqualsIgnoreCase(args[argIndex], "-model"))
{
modelPath = args[argIndex + 1];
argIndex += 2;
}
else
{
if (Sharpen.Runtime.EqualsIgnoreCase(args[argIndex], "-testTreebank"))
{
Pair <string, IFileFilter> treebankDescription = ArgUtils.GetTreebankDescription(args, argIndex, "-testTreebank");
argIndex = argIndex + ArgUtils.NumSubArgs(args, argIndex) + 1;
testTreebankPath = treebankDescription.First();
testTreebankFilter = treebankDescription.Second();
}
else
{
if (Sharpen.Runtime.EqualsIgnoreCase(args[argIndex], "-output"))
{
outputPath = args[argIndex + 1];
argIndex += 2;
}
else
{
unusedArgs.Add(args[argIndex++]);
}
}
}
}
if (modelPath == null)
{
throw new ArgumentException("Need to specify -model");
}
if (testTreebankPath == null)
{
throw new ArgumentException("Need to specify -testTreebank");
}
if (outputPath == null)
{
throw new ArgumentException("Need to specify -output");
}
string[] newArgs = Sharpen.Collections.ToArray(unusedArgs, new string[unusedArgs.Count]);
LexicalizedParser lexparser = ((LexicalizedParser)LexicalizedParser.LoadModel(modelPath, newArgs));
Treebank testTreebank = null;
if (testTreebankPath != null)
{
log.Info("Reading in trees from " + testTreebankPath);
if (testTreebankFilter != null)
{
log.Info("Filtering on " + testTreebankFilter);
}
testTreebank = lexparser.GetOp().tlpParams.MemoryTreebank();
testTreebank.LoadPath(testTreebankPath, testTreebankFilter);
log.Info("Read in " + testTreebank.Count + " trees for testing");
}
FileWriter @out = new FileWriter(outputPath);
BufferedWriter bout = new BufferedWriter(@out);
log.Info("Parsing " + testTreebank.Count + " trees");
int count = 0;
IList <FindNearestNeighbors.ParseRecord> records = Generics.NewArrayList();
foreach (Tree goldTree in testTreebank)
{
IList <Word> tokens = goldTree.YieldWords();
IParserQuery parserQuery = lexparser.ParserQuery();
if (!parserQuery.Parse(tokens))
{
throw new AssertionError("Could not parse: " + tokens);
}
if (!(parserQuery is RerankingParserQuery))
{
throw new ArgumentException("Expected a LexicalizedParser with a Reranker attached");
}
RerankingParserQuery rpq = (RerankingParserQuery)parserQuery;
if (!(rpq.RerankerQuery() is DVModelReranker.Query))
{
throw new ArgumentException("Expected a LexicalizedParser with a DVModel attached");
}
DeepTree tree = ((DVModelReranker.Query)rpq.RerankerQuery()).GetDeepTrees()[0];
SimpleMatrix rootVector = null;
foreach (KeyValuePair <Tree, SimpleMatrix> entry in tree.GetVectors())
{
if (entry.Key.Label().Value().Equals("ROOT"))
{
rootVector = entry.Value;
break;
}
}
if (rootVector == null)
{
throw new AssertionError("Could not find root nodevector");
}
@out.Write(tokens + "\n");
@out.Write(tree.GetTree() + "\n");
for (int i = 0; i < rootVector.GetNumElements(); ++i)
{
@out.Write(" " + rootVector.Get(i));
}
@out.Write("\n\n\n");
count++;
if (count % 10 == 0)
{
log.Info(" " + count);
}
records.Add(new FindNearestNeighbors.ParseRecord(tokens, goldTree, tree.GetTree(), rootVector, tree.GetVectors()));
}
log.Info(" done parsing");
IList <Pair <Tree, SimpleMatrix> > subtrees = Generics.NewArrayList();
foreach (FindNearestNeighbors.ParseRecord record in records)
{
foreach (KeyValuePair <Tree, SimpleMatrix> entry in record.nodeVectors)
{
if (entry.Key.GetLeaves().Count <= maxLength)
{
subtrees.Add(Pair.MakePair(entry.Key, entry.Value));
}
}
}
log.Info("There are " + subtrees.Count + " subtrees in the set of trees");
PriorityQueue <ScoredObject <Pair <Tree, Tree> > > bestmatches = new PriorityQueue <ScoredObject <Pair <Tree, Tree> > >(101, ScoredComparator.DescendingComparator);
for (int i_1 = 0; i_1 < subtrees.Count; ++i_1)
{
log.Info(subtrees[i_1].First().YieldWords());
log.Info(subtrees[i_1].First());
for (int j = 0; j < subtrees.Count; ++j)
{
if (i_1 == j)
{
continue;
}
// TODO: look at basic category?
double normF = subtrees[i_1].Second().Minus(subtrees[j].Second()).NormF();
bestmatches.Add(new ScoredObject <Pair <Tree, Tree> >(Pair.MakePair(subtrees[i_1].First(), subtrees[j].First()), normF));
if (bestmatches.Count > 100)
{
bestmatches.Poll();
}
}
IList <ScoredObject <Pair <Tree, Tree> > > ordered = Generics.NewArrayList();
while (bestmatches.Count > 0)
{
ordered.Add(bestmatches.Poll());
}
Java.Util.Collections.Reverse(ordered);
foreach (ScoredObject <Pair <Tree, Tree> > pair in ordered)
{
log.Info(" MATCHED " + pair.Object().second.YieldWords() + " ... " + pair.Object().Second() + " with a score of " + pair.Score());
}
log.Info();
log.Info();
bestmatches.Clear();
}
/*
* for (int i = 0; i < records.size(); ++i) {
* if (i % 10 == 0) {
* log.info(" " + i);
* }
* List<ScoredObject<ParseRecord>> scored = Generics.newArrayList();
* for (int j = 0; j < records.size(); ++j) {
* if (i == j) continue;
*
* double score = 0.0;
* int matches = 0;
* for (Map.Entry<Tree, SimpleMatrix> first : records.get(i).nodeVectors.entrySet()) {
* for (Map.Entry<Tree, SimpleMatrix> second : records.get(j).nodeVectors.entrySet()) {
* String firstBasic = dvparser.dvModel.basicCategory(first.getKey().label().value());
* String secondBasic = dvparser.dvModel.basicCategory(second.getKey().label().value());
* if (firstBasic.equals(secondBasic)) {
++matches;
* double normF = first.getValue().minus(second.getValue()).normF();
* score += normF * normF;
* }
* }
* }
* if (matches == 0) {
* score = Double.POSITIVE_INFINITY;
* } else {
* score = score / matches;
* }
* //double score = records.get(i).vector.minus(records.get(j).vector).normF();
* scored.add(new ScoredObject<ParseRecord>(records.get(j), score));
* }
* Collections.sort(scored, ScoredComparator.ASCENDING_COMPARATOR);
*
* out.write(records.get(i).sentence.toString() + "\n");
* for (int j = 0; j < numNeighbors; ++j) {
* out.write(" " + scored.get(j).score() + ": " + scored.get(j).object().sentence + "\n");
* }
* out.write("\n\n");
* }
* log.info();
*/
bout.Flush();
@out.Flush();
@out.Close();
}
