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Kaljurand / owl-verbalizer

OWL verbalizer: making machine-readable knowledge also human-readable
http://attempto.ifi.uzh.ch/site/docs/owl_to_ace.html
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ace owl swi-prolog web-ontology-language

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OWL verbalizer

Introduction

OWL verbalizer is a tool that converts an OWL ontology into an Attempto Controlled English (ACE) text.

It can handle complex OWL formulas such as

man
    and (not (own some car))
    and (own some bike)
SubClassOf inverse (likes) some ({Mary})

by turning them into natural English sentences such as:

Every man
    that owns a bike
    and
    that does not own a car
is liked by Mary .

This conversion is designed to be reversible, i.e. one can convert the ACE representation back into OWL so that no loss in meaning occurs. For more of the theory and design choices behind the verbalization read section 5.6 Verbalizing OWL in ACE of

Kaarel Kaljurand. Attempto Controlled English as a Semantic Web Language. PhD thesis, Faculty of Mathematics and Computer Science, University of Tartu, 2007. http://attempto.ifi.uzh.ch/site/pubs/papers/phd_kaljurand.pdf

For a demo visit the OWL verbalizer demo page.

OWL verbalizer is implemented in SWI-Prolog. It offers a command-line front-end and can also be run as an HTTP server. The following example demonstrates launching the server and using it to verbalize an OWL/XML ontology from a remote repository.

$ ./owl_to_ace.exe -httpserver -port 5123 &

$ curl 'http://mowl-power.cs.man.ac.uk:8080/converter/convert?
    ontology=http://protege.stanford.edu/ontologies/pizza/pizza.owl&format=OWL/XML'
| curl -F "xml=<-" http://localhost:5123

The resulting ACE text will appear in STDOUT.

Example

The OWL verbalizer takes its input in OWL 2 XML and produces an output in a fragment of Attempto Controlled English (ACE).

Note that the input must be in OWL 2 XML (http://www.w3.org/TR/owl2-xml-serialization/). No RDF-based format is supported as input. You can convert OWL RDF/XML into OWL 2 XML using the OWL-API v3 (http://owlapi.sourceforge.net/), e.g. via the online tool http://owl.cs.manchester.ac.uk/converter/ or via Protege 4.1+ (http://protege.stanford.edu/).

Input

<?xml version="1.0" encoding="UTF-8"?>
<Ontology
    xmlns="http://www.w3.org/2002/07/owl#"
    xml:base="http://www.w3.org/2002/07/owl#"
    xmlns:xml="http://www.w3.org/XML/1998/namespace">
  <Prefix name="" IRI="http://www.example.org/test#"/>
  <SubClassOf>
    <ObjectIntersectionOf>
      <Class abbreviatedIRI=":man"/>
      <ObjectSomeValuesFrom>
    <ObjectProperty abbreviatedIRI=":own"/>
    <Class abbreviatedIRI=":bike"/>
      </ObjectSomeValuesFrom>
      <ObjectComplementOf>
    <ObjectSomeValuesFrom>
      <ObjectProperty abbreviatedIRI=":own"/>
      <Class abbreviatedIRI=":car"/>
    </ObjectSomeValuesFrom>
      </ObjectComplementOf>
    </ObjectIntersectionOf>
    <ObjectSomeValuesFrom>
      <ObjectInverseOf>
    <ObjectProperty abbreviatedIRI=":like"/>
      </ObjectInverseOf>
      <ObjectOneOf>
    <NamedIndividual abbreviatedIRI=":Mary"/>
      </ObjectOneOf>
    </ObjectSomeValuesFrom>
  </SubClassOf>
</Ontology>

Output

In ace-format:

Every man that own a bike and that does not own a car is like by Mary.

In csv-format:

ignored Prefix(,http://www.example.org/test#)

f   Every
cn_sg   http://www.example.org/test#man
f   that
tv_sg   http://www.example.org/test#own
f   a
cn_sg   http://www.example.org/test#bike
f   and
f   that
f   does
f   not
tv_pl   http://www.example.org/test#own
f   a
cn_sg   http://www.example.org/test#car
f   is
tv_vbg  http://www.example.org/test#like
f   by
pn_sg   http://www.example.org/test#Mary
f   .

Dependencies

The OWL verbalizer depends on a reasonably recent version of SWI-Prolog (http://www.swi-prolog.org/), e.g. 5.10 or higher. SWI-Prolog must be installed together with the packages clib, sgml, and http.

See also: docs/installing_swipl_on_linux.txt.

Compiling the OWL verbalizer command-line client

First, make sure that the SWI-Prolog executable is on the PATH, i.e. that you can execute swipl in any directory.

In order to compile the OWL verbalizer executable, execute:

swipl -O -f owl_to_ace.pl -g "qsave_program('owl_to_ace.exe', [goal(main), toplevel(halt)])." -t halt

or, alternatively, just click on make_exe.bat (on Windows) or type sh make_exe.sh (on Unix / Linux / MacOS X). As a result, an EXE-file (the command-line client) is created.

Using the OWL verbalizer command-line client

The command-line client takes one obligatory argument: the name of the OWL 2 XML file to be verbalized. In the following example, we are using examples/example.owl as input.

./owl_to_ace.exe -xml examples/example.owl

The output (i.e. the resulting ACE text) is printed to standard output.

Note that this command can be also executed as:

swipl -x owl_to_ace.exe -- -xml examples/example.owl

This you can use on computers where the path to SWI-Prolog is different than the one that you used during building.

If executing the EXE-file results in an "out of stack" error, then increase the stack sizes and recompile.

Using the OWL verbalizer webservice

The OWL verbalizer webservice is launched on the command-line, e.g.:

./owl_to_ace.exe -httpserver -port 5123 -workers 2

A good way to start the service on a Unix command-line is:

nohup swipl -x owl_to_ace.exe -- -httpserver -port 5123 -workers 2 > stdout.txt 2> stderr.txt &

In this case, the service is started in the background, a start up message is stored in stdout.txt, and possible error messages in stderr.txt. On Mac OS X, one could use launchctl instead.

As a result, a webserver (SWI HTTP server) is started on port 5123 with 2 worker threads. The optimal number of workers depends on the number of CPUs.

In order to verbalize an ontology, post the OWL 2 XML document to the server via the argument xml. Following are some examples of using curl to achieve this.

curl -F "xml=@examples/example.owl" http://localhost:5123

curl -F "xml=<examples/example.owl" http://localhost:5123

cat examples/example.owl | curl -F "xml=<-" http://localhost:5123

curl 'http://owl.cs.manchester.ac.uk/repository/download?ontology=http://www.co-ode.org/ontologies/pizza/pizza.owl&format=OWL/XML' | curl -F "xml=<-" http://localhost:5123

Posting from an HTML page: look at the source code of docs/owl_to_ace.html.

Posting from Java: use the OWL verbalizer Java interface, in directory java/.

How are OWL entity IRIs verbalized?

The OWL verbalizer maps OWL entity IRIs to ACE content words such that

There are 6 morphological categories that determine the surface form of an IRI:

The user has full control over the eventual surface forms of the IRIs but has to choose them in terms of the above categories. Furthermore,

Using the lexicon

It is possible to specify the mapping of IRIs to surface forms using the following annotation properties:

For example, the following axioms state that if the IRI "#man" is used as a plural common noun, then the wordform men must be used by the verbalizer. If, however, it is used as a singular transitive verb, then mans must be used.

<AnnotationAssertion>
    <AnnotationProperty IRI="http://attempto.ifi.uzh.ch/ace_lexicon#CN_pl"/>
    <IRI>#man</IRI>
    <Literal datatypeIRI="&xsd;string">men</Literal>
</AnnotationAssertion>

<AnnotationAssertion>
    <AnnotationProperty IRI="http://attempto.ifi.uzh.ch/ace_lexicon#TV_sg"/>
    <IRI>#man</IRI>
    <Literal datatypeIRI="&xsd;string">mans</Literal>
</AnnotationAssertion>

For example, these axioms support the generation of the sentence John mans at most 3 men. from an axiom that uses the IRI "#man" via punning once as an object property name, and once as a class name.

If the mapping of an IRI is missing then its fragment is used in the output. The fragment is the part that comes after '#' or the last '/'. Note that this means that different IRIs are not necessarily verbalized as different.

Not using the lexicon (and leaving the IRIs as they are)

If the output-mode is "csv", then each ACE token is output on a separate line and morphological mappings are left to the user to be applied after the verbalization. An example of csv-output is:

pn_sg   http://www.example.org/story.owl#John
f   is
f   a
cn_sg   http://www.example.org/story.owl#man
f   .

f   Every
f   thing
f   that
f   is
f   a
cn_sg   http://www.example.org/story.owl#apple
f   or
f   that
f   is
f   a
cn_sg   http://www.example.org/story.owl#leaf
f   is
f   a
cn_sg   http://www.example.org/story.owl#food
f   .

The columns are tab-separated. The first column specifies the type of the token, e.g.

and the 2nd column contains ACE tokens and OWL IRIs. Empty line denotes axiom borders (each OWL axiom in the input ontology is verbalized by 0 or more ACE sentences).

In this mode the AnnotationAssertions are ignored and IRI fragments are not generated. As a result this mode is about 3x faster.

API-level access to the OWL verbalizer

The API-level access to the OWL verbalizer is only documented with SWI-Prolog's PlDoc. Provided that you have PlDoc installed (SWI-Prolog package pldoc), you can view the documentation by:

?- doc_server(8000).
?- [owl_to_ace].
?- doc_browser.

The main entry point to the verbalizer is the module axiom_sentencelist.pl which converts an input OWL axiom (Prolog term in OWL FSS) to a list of ACE sentences (where each sentence is a Prolog list of ACE tokens, where each token is a Prolog atom, number, or unary ground term).

Tools that use the OWL verbalizer

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