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Statistical parsing of English sentences

, 13 Dec 2006
Shows how to generate parse trees for English language sentences, using a C# port of OpenNLP, a statistical natural language parsing library.
englishparsing_bin.zip
Lithium.dll
ModelConverter.exe
OpenNLP Tools.chm
OpenNLP.dll
ParseTree.exe
SharpEntropy.dll
ToolsExample.exe
englishparsing_net2_0_bin.zip
ToolsExample.exe
Lithium.dll
ModelConverter.exe
OpenNLP Tools.chm
OpenNLP.dll
ParseTree.exe
SharpEntropy.dll
englishparsing_net2_0_src.zip
Lithium
Collections
Delegates
Enums
Interfaces
IO
Lithium.csproj.vspscc
LithiumControl.bmp
Shapes
UI
Visitors
ModelConverter
App.ico
ModelConverter.csproj.vspscc
ParseTree
App.ico
ParseTree.csproj.vspscc
ToolsExample
App.ico
ToolsExample.csproj.vspscc
OpenNLP
OpenNLP.csproj.vspscc
SharpEntropy.dll
Tools
Chunker
NameFind
Parser
PosTagger
SentenceDetect
Tokenize
Util
englishparsing_src.zip
Lithium.csproj.user
LithiumControl.bmp
App.ico
ModelConverter.csproj.user
OpenNLP.csproj.user
SharpEntropy.dll
vssver.scc
vssver.scc
vssver.scc
vssver.scc
vssver.scc
vssver.scc
vssver.scc
App.ico
ParseTree.csproj.user
App.ico
ToolsExample.csproj.user
//Copyright (C) 2005 Richard J. Northedge
//
// This library is free software; you can redistribute it and/or
// modify it under the terms of the GNU Lesser General Public
// License as published by the Free Software Foundation; either
// version 2.1 of the License, or (at your option) any later version.
//
// This library is distributed in the hope that it will be useful,
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Lesser General Public License for more details.
//
// You should have received a copy of the GNU Lesser General Public
// License along with this program; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.

//This file is based on the NameFinderME.java source file found in the
//original java implementation of OpenNLP.  That source file contains the following header:

//Copyright (C) 2003 Thomas Morton
// 
//This library is free software; you can redistribute it and/or
//modify it under the terms of the GNU Lesser General Public
//License as published by the Free Software Foundation; either
//version 2.1 of the License, or (at your option) any later version.
// 
//This library is distributed in the hope that it will be useful,
//but WITHOUT ANY WARRANTY; without even the implied warranty of
//MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
//GNU Lesser General Public License for more details.
// 
//You should have received a copy of the GNU Lesser General Public
//License along with this program; if not, write to the Free Software
//Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.

using System;
using System.Collections;
using OpenNLP.Tools.Util;

namespace OpenNLP.Tools.NameFind
{
	/// <summary>
	/// Class for creating a maximum-entropy-based name finder.
	/// </summary>
	public class MaximumEntropyNameFinder : INameFinder
	{
		private SharpEntropy.IMaximumEntropyModel mModel;
		private INameContextGenerator mContextGenerator;
		private Sequence mBestSequence;
		private BeamSearch mBeam;
		
		public const string Start = "start";
		public const string Continue = "cont";
		public const string Other = "other";
		
		/// <summary>
		/// Creates a new name finder with the specified model.
		/// </summary>
		/// <param name="model">
		/// The model to be used to find names.
		/// </param>
		public MaximumEntropyNameFinder(SharpEntropy.IMaximumEntropyModel model) : this(model, new DefaultNameContextGenerator(10), 10)
		{
		}
		
		/// <summary>
		/// Creates a new name finder with the specified model and context generator.
		/// </summary>
		/// <param name="model">
		/// The model to be used to find names.
		/// </param>
		/// <param name="contextGenerator">
		/// The context generator to be used with this name finder.
		/// </param>
		public MaximumEntropyNameFinder(SharpEntropy.IMaximumEntropyModel model, INameContextGenerator contextGenerator) : this(model, contextGenerator, 10)
		{
		}
		
		/// <summary>
		/// Creates a new name finder with the specified model and context generator.
		/// </summary>
		/// <param name="model">
		/// The model to be used to find names.
		/// </param>
		/// <param name="contextGenerator">
		/// The context generator to be used with this name finder.
		/// </param>
		/// <param name="beamSize">
		/// The size of the beam to be used in decoding this model.
		/// </param>
		public MaximumEntropyNameFinder(SharpEntropy.IMaximumEntropyModel model, INameContextGenerator contextGenerator, int beamSize)
		{
			mModel = model;
			mContextGenerator = contextGenerator;
			mBeam = new NameBeamSearch(this, beamSize, contextGenerator, model, beamSize);
		}
		
		public virtual ArrayList Find(ArrayList tokens, IDictionary previousTags)
		{
			mBestSequence = mBeam.BestSequence(tokens, new object[]{previousTags});
			return new ArrayList(mBestSequence.Outcomes);
		}
		
		public virtual string[] Find(object[] tokens, IDictionary previousTags)
		{
			mBestSequence = mBeam.BestSequence(tokens, new object[]{previousTags});
			ArrayList outcomes = new ArrayList(mBestSequence.Outcomes);
			return (string[]) outcomes.ToArray(typeof(string));
		}
		
		/// <summary>
		/// This method determines wheter the outcome is valid for the preceding sequence.  
		/// This can be used to implement constraints on what sequences are valid.  
		/// </summary>
		/// <param name="outcome">
		/// The outcome.
		/// </param>
		/// <param name="sequence">
		/// The preceding sequence of outcome assignments. 
		/// </param>
		/// <returns>
		/// true is the outcome is valid for the sequence, false otherwise.
		/// </returns>
		protected internal virtual bool ValidOutcome(string outcome, Sequence sequence)
		{
			if (outcome == Continue)
			{
				string[] tags = sequence.Outcomes.ToArray();
				int lastTag = tags.Length - 1;
				if (lastTag == -1)
				{
					return false;
				}
				else if (tags[lastTag] == Other)
				{
					return false;
				}
			}
			return true;
		}
		
		/// <summary>
		/// Implementation of the abstract beam search to allow the name finder to use the common beam search code. 
		/// </summary>
		private class NameBeamSearch : BeamSearch
		{
			private MaximumEntropyNameFinder mNameFinder;
						
			/// <summary>
			/// Creates a beam seach of the specified size using the specified model with the specified context generator.
			/// </summary>
			/// <param name="nameFinder">
			/// The associated MaximumEntropyNameFinder instance.
			/// </param>
			/// <param name="size">
			/// The size of the beam.
			/// </param>
			/// <param name="contextGenerator">
			/// The context generator used with the specified model.
			/// </param>
			/// <param name="model">
			/// The model used to determine names.
			/// </param>
			/// <param name="beamSize">
			/// The size of the beam to use in searching.
			/// </param>
			public NameBeamSearch(MaximumEntropyNameFinder nameFinder, int size, INameContextGenerator contextGenerator, SharpEntropy.IMaximumEntropyModel model, int beamSize) : base(size, contextGenerator, model, beamSize)
			{
				mNameFinder = nameFinder;
			}
			
			protected internal override bool ValidSequence(int index, ArrayList sequence, Sequence outcomeSequence, string outcome)
			{
				return mNameFinder.ValidOutcome(outcome, outcomeSequence);
			}
		}
		
		/// <summary>
		/// Populates the specified array with the probabilities of the last decoded sequence.  The
		/// sequence was determined based on the previous call to <code>chunk</code>.  The 
		/// specified array should be at least as large as the numbe of tokens in the previous call to <code>chunk</code>.
		/// </summary>
		/// <param name="probabilities">
		/// An array used to hold the probabilities of the last decoded sequence.
		/// </param>
		public virtual void GetProbabilities(double[] probabilities)
		{
			mBestSequence.GetProbabilities(probabilities);
		}
		
		/// <summary>
		/// Returns an array with the probabilities of the last decoded sequence.  The
		/// sequence was determined based on the previous call to <code>chunk</code>.
		/// </summary>
		/// <returns>
		/// An array with the same number of probabilities as tokens were sent to <code>chunk</code>
		/// when it was last called.   
		/// </returns>
		public virtual double[] GetProbabilities()
		{
			return mBestSequence.GetProbabilities();
		}
		
		private static SharpEntropy.GisModel Train(SharpEntropy.ITrainingEventReader eventReader, int iterations, int cutoff)
		{
			SharpEntropy.GisTrainer trainer = new SharpEntropy.GisTrainer();
			trainer.TrainModel(iterations, new SharpEntropy.TwoPassDataIndexer(eventReader, cutoff));
			return new SharpEntropy.GisModel(trainer);
		}
		
		public static SharpEntropy.GisModel TrainModel(string trainingFile)
		{
			return TrainModel(trainingFile, 100, 5);
		}

		public static SharpEntropy.GisModel TrainModel(string trainingFile, int iterations, int cutoff)
		{
			SharpEntropy.ITrainingEventReader eventReader = new NameFinderEventReader(new SharpEntropy.PlainTextByLineDataReader(new System.IO.StreamReader(trainingFile)));
			return Train(eventReader, iterations, cutoff);
		}
	}
}

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About the Author

Richard Northedge
Web Developer
United Kingdom United Kingdom
Richard Northedge is a senior developer with a UK Microsoft Gold Partner company. He has a postgraduate degree in English Literature, has been programming professionally since 1998 and has been an MCSD since 2000.

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