Skip to content

Latest commit

 

History

History
141 lines (102 loc) · 4.3 KB

README.md

File metadata and controls

141 lines (102 loc) · 4.3 KB
Raw

CogComp Quantifier

This tool takes plain, unannotated text as input and detects mentions of quantities in the text, as well as normalizes it to a standard form. The program has two compenents connected in a pipeline:

  1. An LBJava classifier which detects spans of text containing quantities.
  2. A rule based normalizer which coverts quantities to a standard form.

This distribution contains the LBJava and Java source code for the quantifier and also allows for training the model using your own training data.

Requirements

Compiling the CogComp Quantifier requires Java 1.6 or higher. If you use it a maven (sbt, etc) dependency, you need Java 1.8.

Installation

CogComp Quantifier can be downloaded from http://cogcomp.cs.illinois.edu/page/software_view/Quantifier.

Running the CogComp Quantifier

Generating Quantities for plain text file

The CogComp Quantifier comes bundled with a program that takes a plain, unannotated text file as input and produces that same text with standardized quantity annotations as output. To invoke this program, type:

java -cp target/classes/:target/dependency/*
edu.illinois.cs.cogcomp.quant.driver.Quantifier <plainTextFile>
<doesNormalize(Y/N)>

When doesNormalize is set to N, no normalization is done, only spans of text with quantities is detected. When set to Y, complete normalization is done.

PROGRAMMATIC USE

To include in a Maven project, use the following dependency and repository declarations in your project's pom.xml file:

<dependencies>
    ...
    <dependency>
        <groupId>edu.illinois.cs.cogcomp</groupId>
        <artifactId>illinois-quantifier</artifactId>
        <version>VERSION</version>
    </dependency>
    ...
</dependencies>
<repositories>
    <repository>
        <id>CogCompSoftware</id>
        <name>CogCompSoftware</name>
        <url>http://cogcomp.org/m2repo/</url>
    </repository>
</repositories>

and replace VERSION with our current version. If you do not have Maven, you can add the jar file illinois-quantifier-2.0.1.jar in target/ folder to your classpath.

Using Locally

Quantifier quantifier = new Quantifier();
List<QuantSpan> quantSpans = quantifier.getSpans(<text>, true);
for(QuantSpan qs : quantSpans) {
    System.out.println("Quantity : "+qs.toString());		  
}

Compiling the Code and Retraining

Note: To compile the code and lbjava files you need to have Maven installed on your system. To download Maven, visit http://maven.apache.org/download.cgi

From the main directory, run :

  sh scripts/train.sh

This downloads all dependencies, trains the model, and compiles all the source files. The training data is provided in data/trainData.txt

Training Details

The provided model is trained on annotated data, which is provided with this distribution. The data is in data/train.txt, and follows the CoNLL 2000 format. The annotations required are BIO tags for each token of sentences, indicating the span of text. The valid tags are as follows :

  Tag       Explanation: "The chunker predicts the word ..."
  B-DATE      begins a date mention or daterange mention.
  I-DATE      is inside a date mention or daterange mention.
  B-RATIO     begins a ratio mention.
  I-RATIO     is inside a ratio mention.
  B-RANGE     begins a range mention (representing a range of (non-date)values).
  I-RANGE     is inside a range mention (representing a range of (non-date)values).
  B-NUM       begins a quantity mention, not falling in the above categories.
  I-NUM       is inside a quantity mention, not falling in the above categories.
  O           is outside of any quantity mention.

3.3.2 Training on new data

You will need to generate the data in CoNLL format (same as data/train.txt). Add the location in src/main/java/edu/illinois/cs/cogcomp/quant/lbj/Constants.java, and recompile.

Citation

If this software is used, please cite the following paper:

Reasoning about Quantities in Natural Language
   Subhro Roy, Tim Vieira and Dan Roth
   TACL 2015

Troubleshooting and Reporting Problems

Simply open an issue in this repository.

Credits

Copyright (C) 2012, Subhro Roy and Dan Roth Cognitive Computation Group Department of Computer Science, University of Illinois at Urbana-Champaign http://cogcomp.cs.illinois.edu/page/software_view/Chunker