OWL verbalizer: making machine-readable knowledge also human-readable
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docs Update doc and improve tests Sep 19, 2013
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java Minor fixes Jul 30, 2012
ontologies Nouns as object properties Sep 18, 2013
tools Updated clex_to_owl.pl to generate the correct OWL 2 XML format. Aug 2, 2011
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axiom_sentencelist.pl * Improved the (PlDoc) documentation, mostly the formatting of it. Jun 13, 2011
build.xml Nouns as object properties Sep 18, 2013
lexicon.pl Nouns as object properties Sep 18, 2013
lexicon_with_assert.pl * Lexicon is now based on non-backtrackable global variables. Jun 9, 2011
make_exe.bat The scripts for compiling the OWL verbalizer executable are Jun 11, 2011
make_exe.sh The scripts for compiling the OWL verbalizer executable are Jun 11, 2011
output_results.pl * Improved the (PlDoc) documentation, mostly the formatting of it. Jun 13, 2011
owl_to_ace.pl Update version number to 0.9.5 Dec 20, 2013
owlace_dcg.pl Checked if the OWL verbalizer works with Yap (v5.3.1). Everything in … Jun 15, 2011
owlxml_owlfss.pl * Improved the documentation Jun 13, 2011
rewrite_subclassof.pl * Improved the (PlDoc) documentation, mostly the formatting of it. Jun 13, 2011
run_tests.py run_tests.py can now test a remote service Jul 30, 2012
table_1.pl Checked if the OWL verbalizer works with Yap (v5.3.1). Everything in … Jun 15, 2011
test.sh Nouns as object properties Sep 18, 2013


OWL verbalizer


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

	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
	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?
| curl -F "xml=<-" http://localhost:5123

The resulting ACE text will appear in STDOUT.


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/).


<?xml version="1.0" encoding="UTF-8"?>
  <Prefix name="" IRI="http://www.example.org/test#"/>
      <Class abbreviatedIRI=":man"/>
    <ObjectProperty abbreviatedIRI=":own"/>
    <Class abbreviatedIRI=":bike"/>
      <ObjectProperty abbreviatedIRI=":own"/>
      <Class abbreviatedIRI=":car"/>
    <ObjectProperty abbreviatedIRI=":like"/>
    <NamedIndividual abbreviatedIRI=":Mary"/>


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	.


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), local(25600), global(25600)])." -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 via options local/1 and global/1, 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

  • OWL individuals map to ACE proper names (PN)
  • OWL classes map to ACE common nouns (CN)
  • OWL properties map to ACE transitive verbs (TV)

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

  • singular form of a proper name (e.g. John)
  • singular form of a common noun (e.g. man)
  • plural form of a common noun (e.g. men)
  • singular form of a transitive verb (e.g. mans)
  • plural form of a transitive verb (e.g. man)
  • past participle form a transitive verb (e.g. manned)

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,

  • the surface forms must be legal ACE content words (e.g. they should not contain punctuation symbols);
  • the mapping of IRIs to surface forms must be bidirectional within the same word class, in order to be able to (if needed) parse the verbalization back into OWL in a semantics preserving way.

Using the lexicon

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

  • http://attempto.ifi.uzh.ch/ace_lexicon#PN_sg
  • http://attempto.ifi.uzh.ch/ace_lexicon#CN_sg
  • http://attempto.ifi.uzh.ch/ace_lexicon#CN_pl
  • http://attempto.ifi.uzh.ch/ace_lexicon#TV_sg
  • http://attempto.ifi.uzh.ch/ace_lexicon#TV_pl
  • http://attempto.ifi.uzh.ch/ace_lexicon#TV_vbg

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.

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

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

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.

  • f = function word
  • qs = quoted string
  • comment = comment
  • cn_sg = singular common noun
  • ...

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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