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RelEx Semantic Relation Extractor

Version 1.6.3 circa 2016

RelEx is a dependency parser for the English language. It extracts dependency relations from Link Grammar, and adds some shallow semantic analysis. The primary use of RelEx is as a language input front-end to the OpenCog artificial general intelligence system.

There are multiple inter-related parts to RelEx. The core component extracts the dependency relationships. An experimental module provides some simple anaphora resolution suggestions. Output is provided in various formats, including one format suitable for later batch post-processing, another format suitable for input to OpenCog, and an W3C OWL format. There are also a small assortment of perl scripts for cleaning up web and wiki pages, &c.

The main RelEx website is at

It provides an overview of the project, as well as detailed documentation.

The source code management system is at

Source tarballs may be downloaded from either of two locations:

Build and install of the core package is discussed below.

Running the Relex Servers

Run via Docker

The easiest way to run RelEx is with Docker. The Docker system allows sandboxed containers to be easily created and deployed; the typical use of a container is to run some server. See the website for more info and tutorials.

Opencog has prebuilt images for relex available with the image tag: opencog/relex

Running the Plain-text Server

To have docker run the plain text server, type into a terminal:

   $ docker run -it -p 3333:3333 opencog/relex /bin/sh

To test the plain text server via telnet, type into another terminal:

   telnet localhost 3333
   This is a test sentence!

The server will return a plain-text analysis of the input sentence and disconnect the session.

Running the OpenCog-format Server

To have docker run the OpenCog format server, type:

   $ docker run -it -p 4444:4444 opencog/relex /bin/sh

To test the OpenCog format server via telnet, type into another terminal:

   telnet localhost 4444
   This is a test sentence!

The server will return an OpenCog/Scheme version of the parse and disconnect the session.

Running the raw Link Grammar Server

To have docker run the raw link-grammar JSON-format server, type:

   $ docker run -it -p 9000:9000 opencog/relex /bin/sh

You can now access the relex server with telnet.

The raw link-grammar server expects a JSON-formatted input, begining with the 5 letters text: it returns a JSON-formatted response.

To test the link-grammar JSON format server via telnet, type into another terminal:

   telnet localhost 9000
   text:This is a test sentence!

This will return a JSON formatted parse and then disconnect the session.

Docker Cheat-Sheet

A docker cheat-sheet:

docker ps
docker ps -a
docker rm
docker images
docker rmi


Installing on Ubuntu/Debian

An installation script for Ubuntu/Debian is provided in the install-scripts directory.

Installing on all other systems

For other systems, follow the instructions below. To build and use RelEx, the following packages are required to be installed:

  • libgetopt-java (GNU getopt)
  • Link Parser
  • WordNet 3.0
  • JWNL Java wordnet library
  • OpenNLP tools (optional, but recommended)
  • W3C OWL (optional)

Pre-requisite dependencies

The following packages are required pre-requisites for building RelEx.

  • Link Grammar Parser. Compile and install the Link Grammar Parser. This parser is described at

    and sources are available for download at

    Link-grammar version 5.2.1 or later is needed to obtain a variety of required fixes.

    The Link Grammar Parser is the underlying engine, providing the core sentence parsing ability.

    If the parser is not installed in the default location, be sure to modify -Djava.library.path appropriately in and other shell scripts.

  • GNU getopt. This is a standard command-line option parsing library. For Ubuntu, install the libgetopt-java package.

  • Wordnet. Wordnet is used by RelEx to provide basic English morphology analysis, such as singular versions of (plural) nouns, base forms (lemmas) of adjectives, adverbs and infinitive forms of verbs.

    Download, unpack and install WordNet 3.0. The install directory needs to be specified in data/wordnet/file_properties.xml, with the name="dictionary_path" property in this file.

    Some typical install locations are:

    • /opt/WordNet-3.0/data for RedHat and SuSE
    • /usr/share/wordnet for Ubuntu and Debian
    • C:\Program Files\WordNet\3.0\data for Windows

    The relex/Morphy/ class provides a simple, easy-to-use wrapper around wordnet, providing the needed word morphology info.

The following packages are required pre-requisites for building RelEx. Note, that they are automatically installed if Maven system is used.

  • didion.jwnl. The didion JWNL is the "Java WordNet Library", and provides the Java programming API to access the wordnet data files. Its home page is at

    and can be downloaded from

    Verify that the final installed location of jwnl.jar is correctly specified in the build.xml file. Note that GATE also provides a jwnl.jar, but the GATE version of jwnl.jar is not compatible (welcome to java DLL hell).

    When copying jwnl.jar: verify the file permisions! Be sure to issue the following command: chmod 644 jwnl.jar, as otherwise, you'll get strange "java cannot unzip jar" error messages.

  • Apache Commons Logging. The JWNL package requires that the Apache commons logging jar file be installed. In Debian/Ubuntu, this is supplied by the libcommons-logging-java package. In RedHat/CentOS systems, the package name is jakarta-commons-logging.

  • SLF4J and Logback. RelEx uses SLF4J as a facade for the Logback logging framework. SLF4J home pages is at

    and can be downloaded from

    Logback home pages is at

    and can be downloaded from

Optional packages

The following packages are optional. If they are found, then additional parts of RelEx will be built, enabling additional function.

If you use Maven, these dependencies are already managed.

  • OpenNLP. RelEx uses OpenNLP for sentence detection, giving RelEx the ability to find sentence boundaries in free text. If OpenNLP is not found, then the (far) less accurate java.text.BreakIterator class is used. Although Oracle documentation states that "Sentence boundary analysis allows selection with correct interpretation of periods within numbers and abbreviations", this is patently false, as it incorrectly breaks the sentence "Dr. Smith is late." into two sentences. Thus, OpenNLP is recommended.

    The OpenNLP home page is at

    Download and install OpenNLP tools, and verify that the installed files are correctly identified in both build.xml and in

    OpenNLP also requires the installation of maxent from

    You'll need maxent-3.0.0.jar and opennlp-tools-1.5.3.jar.

    The OpenNLP package is used solely in corpus/, which provides a simple, easy-to-use wrapper for splitting a document into sentences. Replace this file if an alternate sentence detector is desired.

  • Trove. Some users may require the GNU Trove to enable OpenNLP, although this depends on the JDK installed. GNU Trove is an implementation of the java.util class hierarchy, which may or may not be included in the installed JDK. If needed, download trove from:

    Since trove is optimized, using it may improve performance and/or decrease memory usage, as compared to the standard Sun JDK implementation of the java.util hierarchy.

    IMPORTANT OpenNLP expects Gnu Trove version 1.0, and will not work with version 2.0 !!


With Maven

Maven manages almost all of dependencies automatically. Only exception is Link Grammar library which should be added into local maven repository manually, using:

mvn install:install-file \
    -Dfile=<linkgrammar-jar-folder/linkgrammar.jar> \
    -DgroupId=org.opencog \
    -DartifactId=linkgrammar \
    -Dversion=<linkgrammar.version> \

Then you can build and install relex.jar using:

mvn install

Using RelEx

It is assumed that RelEx will be used in one of two different ways. These are in a "batch processing" mode, and a "custom Java development" mode.

In the "batch processing mode", RelEx is run once over a large text, and its output is saved to a file. This output can then be post-processed at a later time, to extract desired info. The goal here is to avoid the heavy CPU overhead of re-parsing a large text over and over. Example post-processing scripts are included (described below).

In the "custom Java development" mode, it is assumed that a capable Java programmer can write new code to interface RelEx to meet their needs. A good place to start is to review the workings of the output code in src/java/relex/output/*.java.

The standard RelEx demo output is NOT SUITABLE for post-processing. It is meant to be a human-readable example of what the system generates; it does not include all required output. For example, if the same word appears in a sentence twice, the demo output will not distinguish between these two words.

This release of RelEx includes an experimental Stanford-parser compatibility mode. In this mode, RelEx will generate the same dependency relations as the Stanford parser. This mode is technically interesting for comparing output; RelEx is more than three time faster than the lexicalized (factored) Stanford parser, although it is slower than the PCFG parser. This is described in greater detail in the file README-Stanford.

This release of RelEx includes an optional Penn Treebank style part of speech tagger. The tagger is experimental, and has not been evaluated for accuracy. It is probable that the accuracy is low, primarily because it has not been well tested. Because the tagging is based on the syntactic parse, in principle the accuracy could be very high, once fully debugged.

Running RelEx

Several example unix shell scripts and MS Windows batch files are included to show sample usage. These files (*.sh in unix, or *.bat, in Windows) define the required system properties, classpath and JVM options.

If there are any ClassNotFound exceptions, please verify the paths and values in these files.

The primary usage example is the file. Running this will display:

  • The link parser output.
  • The detected persons, organizations and locations.
  • The dependency relations found.
  • Anaphora resolutions.
  • Parse ranking info.
  • (Optionally) Stanford and Penn Treebank output.

Output is controlled by command-line flags that are set in the shell script. The -h flag will print a list of all of the available command-line options.

The script is an example batch processing script. This script outputs the so-called "compact (cff) format" which captures the full range of Link Grammar and RelEx output in a format that can be easily post-processed by other systems (typically by using regex's).

The idea behind the batch processing is that it is costly to parse large quantities of text: thus, it is convenient to parse the text once, save the results, and then perform post-processing at leisure, as needed. Thus, the form of post-processing can be changed at will, without requiring texts to be re-processed over and over again.


This perl script provides an example of post-processing: it converts the "cff" batch output format into OpenCog hypergraphs, which can then be processed by OpenCog.

This script starts a relex server that listens for plain-text input (English sentences) on port 4444. It then parses the text, and returns opencog output on the same socket. This server is meant to serve the OpenCog chatbot directly; it is not intended for general, manual use.

The file is a simple command-line utility to reformat a free-form text into sentences, one per line.


Ad-hoc script to scrub Wikipedia xml dumps, outputting only valid English-language sentences. This script removes wiki markup, URL's tables, images, & etc. It currently seems to be pretty darned bullet-proof, although it might handle multi-line refs incorrectly.

relexd, relexd-relex, relexd-link

If you built RelEx with Maven, these scripts can be used. They accept additional arguments to be passed to relex.Server.

  1. sh target/appassembler/bin/relexd, which runs java relex.Server ...
  2. sh target/appassembler/bin/relexd-relex, which runs java relex.Server --relex ...
  3. sh target/appassembler/bin/relexd-link, which runs relex.Server --link --relex --verbose ...

Using RelEx in custom code

The primary output of RelEx is the set of semantic relationships of a sentence. To obtain the list of these relationships, make a copy of src/java/relex/output/, and customize it to provide the relationships that you wish, in the format that you wish.

The class src/java/relex/ should be considered to be a large example program illustrating all of the various features of RelEx. For custom applications, this class should be copied and modified as desired to fit the application.

Speed test results

Performance comparison of RelEx-1.2.0 vs. Stanford-1.6.1, run 11 Oct 2009. Test corpus: first 150 sentences (including preface boilerplate) from Project Gutenberg "Pride and Prejudice". Due to differences in sentence detection, Stanford and RelEx disagree on the sentence count. Due to differences in counting punctuation, the splitting of possessives and contractions, the two disagree on the word count as well.

Since these tests were run, the performance of link-grammar has been improved by a factor of 2x-3x. This update should have a significant effect on relex speeds.

The unix command wc counts 2609 words in 148 sentences, for 2609/148 = 17.6 words/sent.

Stanford, w/ englishFactored.ser.gz , w/unix time command:

  real	10m4.882s
  user	10m1.974s
  sys	0m4.208s

Actual: 2609/605= 4.31 words/sec

Stanford, w/ englishPCFG.ser.gz , w/unix time command:

  real	2m21.690s
  user	2m23.165s
  sys	0m1.056s

Actual: 2609/143 = 18.24 words/sec

Stanford, w/ wsjFactored.ser.gz , w/unix time command:

  real	10m5.972s
  user	10m3.802s
  sys	0m4.516s

Stanford, w/ wsjPCFG.ser.gz , w/unix time command:

  real	2m11.154s
  user	2m14.312s
  sys	0m1.144s

Actual: 2609/134 = 19.47 words/sec

RelEx, w/unix time command:

  real	2m59.739s
  user	2m36.342s
  sys	0m22.137s

Actual: 2609/180 = 14.50 words/sec

  Ratio: Stanford-englishFactored/RelEx = 605sec/180sc = 3.36x (faster)
  Ratio: Stanford-wsjFactored/RelEx = 606sec/180sec = 3.36x (faster)
  Ratio: Stanford-englishPCFG/RelEx = 143sec/180sec = 0.79x (slower)
  Ratio: Stanford-wsjPCFG/RelEx = 134sec/180sec = 0.74x (slower)


TODO - Comparatives

RelEx is buggy when it comes to handling comparative sentences. This needs fixing.

TODO - Wordnet Install

Windows users consistently have trouble installing Wordnet correctly. In particular, dictionary location appears to be totally random. Try to find some work-around for this.


Sentence splitter: The sentence splitter fails to split the following:

"In such cases, a woman has not often much beauty to think of." "But, my dear, you must indeed go and see Mr. Bingley when he comes into the neighbourhood."


  • write paper on wsd by pos-lookup
  • write paper on relex overview


Lexical Chunking

Key ideas:

  • Lexis is the basis of language.
  • Language consists of grammaticalized lexis, not lexicalized grammar.

See: Olga Moudraia, "Lexical Approach to Second Language Teaching"

Alternate names: "gambits", "lexical phrases", "lexical units", "lexicalized stems", "speech formulae".

Definition of Lexical Chunks

Lexis may be single words, and also the word combinations that are a basis of one's mental lexicon. That is, language consists of meaningful chunks that, when combined, produce continuous coherent text; only a minority of spoken sentences are entirely novel creations.

Types of lexical chunks:

  • Words (e.g., book, pen)
  • Phrasal verbs (e.g. switch off, talk to ... about ...)
  • Polywords (e.g., by the way, upside down)
  • Collocations, or word partnerships (e.g., community service, absolutely convinced)
  • Idioms (e.g. break a leg, back in the day)
  • Institutionalized utterances (e.g., I'll get it; We'll see; That'll do; If I were you . . .; Would you like a cup of coffee?)
  • Sentence frames and heads (e.g., That is not as . . . as you think; The fact/suggestion/problem/danger was . . .)
  • Text frames (e.g., In this paper we explore . . .; Firstly . . .; Secondly . . .; Finally . . .)

(Taken from Lewis, M. (1997b). "Pedagogical implications of the lexical approach." In J. Coady & T. Huckin (Eds.), "Second language vocabulary acquisition: A rationale for pedagogy" (pp. 255-270). Cambridge: Cambridge University Press.)