JarCastingixa-pipe-ml
ixa-pipe-ml is the Machine Learning Component of IXA pipes. ixa-pipe-ml allows to train and evaluate the models for every IXA-pipe available.
ixa-pipe-ml is part of IXA pipes, a multilingual set of NLP tools developed by the IXA NLP Group [http://ixa2.si.ehu.es/ixa-pipes].
Please go to [http://ixa2.si.ehu.es/ixa-pipes] for general information about the IXA pipes tools but also for official releases, including source code and binary packages for all the tools in the IXA pipes toolkit.
This document is intended to be the usage guide of ixa-pipe-ml. If you really need to clone and install this repository instead of using the releases provided in [http://ixa2.si.ehu.es/ixa-pipes], please scroll down to the end of the document for the installation instructions.
NOTICE!!: ixa-pipe-ml is now in Maven Central.
TABLE OF CONTENTS
OVERVIEW
ixa-pipe-ml provides the training and evaluation functionalities required to train and evaluate sequence labeling and constituent parsing models to be used in the ixa pipes modules (http://ixa2.si.ehu.es/ixa-pipes/).
Every model trained with ixa-pipe-ml is self-contained, that is, the properties files are not needed to use them. Please see the sequenceTrainer.properties template file for all available training options and documentation.
ixa-pipe-ml provides competitive models based on robust local features and exploiting unlabeled data via clustering features. The clustering features are based on Brown, Clark (2003) and Word2Vec clustering plus some gazetteers in some cases. The procedure to obtain such clusters is described in (https://github.com/ragerri/cluster-preprocessing). To avoid duplication of efforts, we use and contribute to the API provided by the Apache OpenNLP project with our own custom developed features.
CLI-USAGE
ixa-pipe-ml provides the following command-line basic functionalities:
- sequenceTrainer: trains sequence labeling models for POS tagging, Lemmatization, Named Entity Recognition, Opinion Target Extraction, Chunking and Supersense tagging.
- parserTrainer: trains constituent parsing models.
- eval: evaluates a trained sequence labeling model with a given test set. Accuracy or F1 can be chosen.
- parseval: evaluates a trained parsing model with parseval metric.
- cross: it runs cross validation training.
Each of these functionalities are accessible by as subcommands to the ixa-pipe-ml-$version.jar. Please read below and check the -help parameter:
java -jar target/ixa-pipe-ml-$version-exec.jar (sequenceTrainer|parserTrainer|eval|parseval|cross) -help
### Features
**A description of every feature is provided in the sequenceTrainer.properties properties
file** distributed with ixa-pipe-ml. As the training functionality is configured in
properties files, please do check this document.
### Training
To train a new model you just need to pass a training parameters file as an
argument. As it has been already said, the options are documented in the
template trainParams.properties file.
**Example**:
````shell
java -jar target/ixa.pipe.ml-$version-exec.jar train -p sequenceTrainer.properties
Training with Features using External Resources: For training with dictionary or clustering based features (Brown, Clark and Word2Vec) you need to pass the lexicon as value of the respective feature in the properties file. This is only for training, as for tagging or evaluation the model is serialized with all resources included.
Evaluation
You can evaluate a trained model or a prediction data against a reference data or testset.
- language: provide the language.
- metric: Choose the metric: accuracy or F1.
- model: the model to be evaluated.
- testset: the testset or reference set.
- corpusFormat: the format of the reference set and of the prediction set if --prediction option is chosen.
- evalReport: detail of the evaluation report
- brief: just the F1, precision and recall scores
- detailed, the F1, precision and recall per class
- error: the list of false positives and negatives
Example:
java -jar target/ixa.pipe.nerc-$version-exec.jar eval -m en-local-conll03.bin -l en -f conll03 -t conll03.testb
API
The easiest way to use ixa-pipe-ml programatically is via Apache Maven. Add this dependency to your pom.xml:
<dependency>
<groupId>eus.ixa</groupId>
<artifactId>ixa-pipe-ml</artifactId>
<version>0.0.4</version>
</dependency>
JAVADOC
The javadoc of the module is located here:
ixa-pipe-ml/target/ixa-pipe-ml-$version-javadoc.jar
Module contents
The contents of the module are the following:
+ formatter.xml Apache OpenNLP code formatter for Eclipse SDK
+ pom.xml maven pom file which deals with everything related to compilation and execution of the module
+ src/ java source code of the module and required resources
+ Furthermore, the installation process, as described in the README.md, will generate another directory:
target/ it contains binary executable and other directories
+ trainParams.properties A template properties file containing documention
for every available option
INSTALLATION
Installing the ixa-pipe-ml requires the following steps:
If you already have installed in your machine the Java 1.7+ and MAVEN 3, please go to step 3 directly. Otherwise, follow these steps:
1. Install JDK 1.7 or JDK 1.8
If you do not install JDK 1.7+ in a default location, you will probably need to configure the PATH in .bashrc or .bash_profile:
export JAVA_HOME=/yourpath/local/java7
export PATH=${JAVA_HOME}/bin:${PATH}
If you use tcsh you will need to specify it in your .login as follows:
setenv JAVA_HOME /usr/java/java17
setenv PATH ${JAVA_HOME}/bin:${PATH}
If you re-login into your shell and run the command
java -version
You should now see that your JDK is 1.7 or 1.8.
2. Install MAVEN 3
Download MAVEN 3 from
wget http://apache.rediris.es/maven/maven-3/3.0.5/binaries/apache-maven-3.0.5-bin.tar.gz
Now you need to configure the PATH. For Bash Shell:
export MAVEN_HOME=/home/ragerri/local/apache-maven-3.0.5
export PATH=${MAVEN_HOME}/bin:${PATH}
For tcsh shell:
setenv MAVEN3_HOME ~/local/apache-maven-3.0.5
setenv PATH ${MAVEN3}/bin:{PATH}
If you re-login into your shell and run the command
mvn -version
You should see reference to the MAVEN version you have just installed plus the JDK that is using.
3. Get module source code
If you must get the module source code from here do this:
git clone https://github.com/ixa-ehu/ixa-pipe-ml
4. Compile
Execute this command to compile ixa-pipe-ml:
cd ixa-pipe-ml
mvn clean package
This step will create a directory called target/ which contains various directories and files. Most importantly, there you will find the module executable:
ixa-pipe-ml-$version.jar
This executable contains every dependency the module needs, so it is completely portable as long as you have a JVM 1.7 installed.
To install the module in the local maven repository, usually located in ~/.m2/, execute:
mvn clean install
Contact information
Rodrigo Agerri
IXA NLP Group
University of the Basque Country (UPV/EHU)
E-20018 Donostia-San Sebastián
[email protected]