This presentation describes how the RDF version of the Apertium bilingual dictionaries were modelled, generated, and linked to BabelNet

1. 18/05/2016 1Presenter name
Apertium RDF:
an experience in generating
linguistic linked open data
Jorge Gracia
Ontology Engineering Group (OEG)
Universidad Politécnica de Madrid (UPM)
jgracia@fi.upm.es
1st Summer Datathon on Linguistic Linked Open Data
Cercedilla (Spain), 15-19th June 2015

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Outline
Motivation
The Apertium platform
Representing translations in RDF
Building the Apertium RDF graph
Traversing the graph
Linking with external sources
Conclusions
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Motivation

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Motivation
Current multilingual lexica and electronic dictionaries
• Proprietary formats
• Non‐standard APIs
• Disconnected from other resources
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Motivation
GOAL: to expose translations contained in bilingual
dictionaries as Linked Data on the Web
Joint effort by
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The Apertium platform

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Apertium
Apertium [http://www.apertium.org] open source
platform for Machine Translation. Its bilingual
dictionaries available in XML.
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Apertium
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Afrikaans <-> Dutch
Breton --> French
Catalan <-> Italian
Welsh <-> English
Danish <-- Norwegian
English <-> Catalan
English <-> Spanish
English <-> Galician
Esperanto <-- Catalan
Esperanto <-> English
Esperanto <-- Spanish
Esperanto <-- French
Spanish <-> Aragonese
Spanish <-> Asturian
Spanish <-> Catalan
Spanish <-> Galician
Spanish <-> Italian
Spanish <-> Portuguese
Spanish <-> Romanian
Basque --> English
Basque --> Spanish
French <-> Catalan
French <-> Spanish
Serbo-Croatian <-> English
Serbo-Croatian <-> Macedonian
Serbo-Croatian <-> Slovenian
Indonesian <-> Malaysian
Icelandic <-> Swedish
Icelandic --> English
Kazakh <-> Tatar
Macedonian <-> Bulgarian
Macedonian --> English
Norwegian Nynorsk <-> Norwegian
Bokmål
Occitan <-> Catalan
Occitan <-> Spanish
Portuguese <-> Catalan
Portuguese <-> Galician
Northern Sami --> Norwegian
Bokmål
Swedish <-> Danish
……
More that 40 language pairs
22 of them (more stable) available in LMF

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Representing translations
in RDF

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lemon
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LexicalSense
trans
translationTarget
context
TranslationSet Translation
translationConfidence:double
The translation module
Translation Categories
http://purl.org/net/translation-categories
translationCategory
context
Resource
http://purl.org/net/translation.owl
Translation Module
translationSource
directEquivalent
culturalEquivalent
lexicalEquivalent
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lemon:LexicalEntry
lemon:LexicalEntry
lemon:LexicalSense
lemon:LexicalSense
lemon:Lexicon
lexiconEN
lemon:Lexicon
lexiconES
tr:Translation
“bench”@en
“banco”@es
lemon:entry
lemon:entry
lemon:isSenseOf
lemon:isSenseOf tr:translationTarget
tr:translationSource
tr:trans
lemon:lexicalForm
lemon:lexicalForm
lemon:Form
lemon:Form
lemon:writtenRep
tr:TranslationSet
translationSetEN‐ES
lemon:writtenRep
Translation example

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Building the
Apertium RDF graph

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Methodology
1. Data analysis and vocabulary selection
2. Modelling
3. URIs design
4. RDF generation
5. Publication as linked data
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Modelling
Mapping of data sources

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URIs design
# Apertium English lexicon:
http://linguistic.linkeddata.es/id/apertium/lexiconEN
# Apertium Spanish lexicon:
http://linguistic.linkeddata.es/id/apertium/lexiconES
# Apertium English-Spanish translation set:
http://linguistic.linkeddata.es/id/apertium/tranSetEN-
ES
Following ISA recommendations
[Archer et al.]:
Archer, P., Goedertier, S., & Loutas, N. (2012). Study on persistent URIs. Tech. rep..

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RDF Generation
RDF generation based on Open Refine
• E.g., RDF generated:
apertium:lexiconEN a lemon:Lexicon ;
dc:source
<http://hdl.handle.net/10230/17110> .
...
apertium:lexiconEN lemon:entry
apertium:lexiconEN/bench-n-en .
apertium:lexiconEN/bench-n-en a lemon:LexicalEntry
;
lemon:lexicalForm apertium:lexiconEN/bench-
n-en-form ;
lexinfo:partOfSpeech lexinfo:noun .
apertium:lexiconEN/bench-n-en-form a lemon:Form ;
lemon:writtenRep "bench"@en .

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Publication
• SPARQL endpoint
http://linguistic.linkeddata.es/apertium/sparql‐
editor/
• Web interface
http://linguistic.linkeddata.es/apertium/
• Datahub
http://datahub.io/dataset?q=apertium+rdf&organiz
ation=oeg‐upm
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Traversing the graph

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22 generated datasets
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Lang. pair # triples # trans.
CA‐IT 180,851 7,869
EN‐CA 759,601 33,029
EN‐ES 576,316 25,830
EN‐GL 425,117 20,034
EO‐CA 426,301 19,964
EO‐EN 617,772 31,474
EO‐ES 380,198 17,212
EO‐FR 726,281 35,791
ES‐AN 71,997 3,110
ES‐AST 825,54 36,096
ES‐CA 730,501 31,291
Lang. pair # triples # trans.
ES‐GL 206,284 8,985
ES‐PT 279,245 12,054
ES‐RO 400,366 17,318
EU‐ES 262,336 11,838
EU‐EN 265,466 13,089
FR‐CA 152,002 6,550
FR‐ES 495,614 21,475
OC‐CA 346,346 15,983
OC‐ES 317,162 14,561
PT‐CA 163,149 7,111
PT‐GL 234,065 10,144

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Apertium RDF in the LLOD cloud
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Apertium RDF in the LLOD cloud

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Direct translations
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Direct translations for “bank”@en
Translated written repr. Part of Speech
"banc"@ca http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"riba"@ca http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"banco"@es http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"orilla"@es http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"ribera"@es http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"beira"@gl http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"banco"@gl http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"ourela"@gl http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"orela"@gl http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"banku"@eu http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"erribera"@eu http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"ertz"@eu http://www.lexinfo.net/ontology/2.0/lexinfo#noun
"amuntegar"@ca http://www.lexinfo.net/ontology/2.0/lexinfo#verb
"agolpar"@es http://www.lexinfo.net/ontology/2.0/lexinfo#verb
"amontonar"@es http://www.lexinfo.net/ontology/2.0/lexinfo#verb
"apelotonar"@es http://www.lexinfo.net/ontology/2.0/lexinfo#verb
"hacinar"@es http://www.lexinfo.net/ontology/2.0/lexinfo#verb
.... ...

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Lexicon CA
Lexicon EN
Lexicon EN
Lexicon ES
Translation
Set EN‐ES
Translation
Set EN‐CA
Apertium LMF
Apertium RDF
EN‐ES
EN‐CA
Monolingual
lexicons
Translation sets
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orilla
“ribera”@es
bank‐
banco
TranslationSetEN‐ESLexiconES LexiconEN
“orilla”@es
banco‐
banco
TranslationSetES‐PT LexiconPT
banco
“banco”@pt
bank
benchribera
orla
bank‐
ribera
bank‐
orilla
bench‐
banco
orilla‐
orla
“bench”@en
“bank”@en
“orla”@pt
banco
“banco”@es

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Indirect translations
Indirect translations for “bank” EN‐> ES ‐> PT
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Pivot translation written repres. Indirect translation written repres.
"banco"@es "banco"@pt
"orilla"@es "orla"@pt

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Apertium RDF graph
Dijkstra algorithm to choose shortest path
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bench
banco
LexiconEN LexiconESLexiconCA
banc
orilla
ribera
bank
riba
How to measure confidence

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One time inverse consultation (OTIC)
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Given a lexical entry s:
1. Get direct translations of s in the pivot language Ps
2.  p  Ps, get its translations in the target language Tp
3. For every t  Tp,
(a) gets its set of translations in the pivot language (Pt)
(b) calculates the score for t:
||||
*2)(
ts
ts
PP
PP
tscore



Tanaka, K., & Umemura, K. (1994). Construction of a bilingual dictionary intermediated by a third
language. In COLING, pp. 297–303.

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bench
banco
LexiconEN LexiconESLexiconCA
banc
orilla
ribera
bank
riba
One time inverse consultation
s = “banco”@es
Pbanco={“bank”@en, “bench”@en}
Tbank={“banc”@ca, “riba”@ca}
Tbench={“banc”@ca}
Pbanc={“bank”@en, “bench”@en}
Priba={“bank”@en}
score(“banc”@ca) = 1.0
score(“riba”@ca) = 0.5

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Linking with external
sources

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Linking to BabelNet
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Around 130.000 links between Apertium RDF – BabelNet

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Linking to BabelNet
Translated
Written Repr.
BabelSynset BabelNet gloss
"banco" @es http://babelnet.org/rdf/s00008371n
“A building in which the business
of banking transacted”
"banco" @es http://babelnet.org/rdf/s00008366n
“An arrangement of similar
objects in a row or in tiers”
"banco" @es http://babelnet.org/rdf/s15346085n
“An ocean bank, sometimes
referred to as a fishing bank or
simply bank, ...”
… … …
"orilla" @es http://babelnet.org/rdf/s00008363n
“Sloping land (especially the
slope beside a body of water)”
"ribera" @es http://babelnet.org/rdf/s00008363n
“Sloping land (especially the
slope beside a body of water)”
Translations for “bank”@en

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Conclusions

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Conclusions
• Apertium data on the Web following SW standards
• Common entry point for all the Apertium dictionaries
• Direct and indirect translations can be easily obtained
via SPARQL
• Confidence degree for indirect translations
• Linked with BabelNet
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Conclusions
Related reading…
http://kdictionaries.com/kdn/kdn23.pdf

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Thanks for your attention !
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http://linguistic.linkeddata.es/apertium/

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Some results of applying OTIC
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Language path Threshold Precision Recall
EN‐CA‐ES
0.0 76% 48%
0.5 77% 48%
1.0 82% 43%
ES‐EN‐CA
0.0 53% 39%
0.5 55% 39%
1.0 61% 36%
EN‐ES‐CA
0.0 73% 38%
0.5 76% 38%
1.0 83% 33%