nliwod iswc 2014 - multilingual retrieval interface for structured data on the web
DESCRIPTION
This presentation described a Multilingual Retrieval Interface for Structured data on the Web, a talk given at NLIWoD workshop at ISWC 2014. The approach is based on Grammatical framework and semantic web and linked data technologiesTRANSCRIPT
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Multilingual Retrieval Interface for Structured Data on the Web
Dana Dannells, Ramona Enache, Mariana Damova
NLIWoD - ISWC’2014
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Semantic Data Infrastructures
Leonardo Mona Lisa
RDF Repository
SPARQL
:Painter :Painting
:painted
Mona Lisa ?
rdf:typ
e
rdf:
typ
e
• Semantic Web • Linked data • SPARQL query language
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Natural Interface through NL
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EN FR DE
Who painted Mona Lisa? Qui a paint Mona Lisa? Wer hat Mona Lisa gemahlt?
Who is Mona Lisa’s painter? Qui est le paintre de Mona Lisa? Wer ist der Mahler von Mona Lisa ?
Who created Mona Lisa? Qui a créé Mona Lisa? Wer hat Mona Lisa geschöpft?
Leonardo da Vinci A:
Q:
NL to ontology interoperability
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Multilingual Retrieval Interface
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GF – Grammar Framework
• Type-theoretical grammar formalism supporting multilingual applications
• Two-layered architecture
– Abstract syntax - semantics
– Concrete syntax – language dependent surface structure
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Abstract syntax: Concrete English syntax: Abstract representation: cat NP, VP, S; lincat NP, VP, S = {s: Str}; lin Mary = mkNP (mkPN "Mary"); fun Mary, John: NP; lin Mary = {s = "Mary"}; lin John = mkNP (mkPN "John"); fun Love: NP -> VP; lin John = {s = "John"}; lin Love o = mkVP (mkV2 "love") o; fun Pred : NP -> VP -> S; lin Love o = {s = "loves" ++ o.s}; lin Pred sub v = mkS (mkCl sub v); lin Pred sub v = {s = sub.s ++ v.s};
Ex: John loves Mary
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Multilingual Aspect of GF
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YAQL (Yet Another Query language)
• A common architecture with one base module and domain knowledge representation
• Straightforward abstract syntax generation from ontology with just the minimum lexical types – Common noun – Kind
– Noun phrase – Entity
– Verb phrase – Property
– Verb phrase with higher arity – Relation
• Reusable generic grammar structure
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Abstract syntax: Concrete syntax: Move ; Move = Utt ; Query ; Query = QS ; MQuery : Query -> Move ;
Query Command Answer
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YAQL and the Semantic Web
The category Kind gets coupled with OWL entities
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• Yet another NL two layers so that a new domain model can be easily integrated into the query module • Bidirectional translation in 15 languages (Bulgarian, Catalan, Danish, Dutch, English, Finnish, French, Hebrew, Italian, German, Norwegian, Romanian, Russian, Spanish, Swedish)
Text Query Answer
Data
Lexicon
RGL
YAQL
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NL to SPARQL
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Who painted Mona Lisa?
English: Who painted t ?
QPainter t = mkQS pastTense (mkQCl who\_IP paint\_V2 t)
Finnish: Whose painting is t ?}
QPainter t = mkQS (mkQCl (mkIP (E.GenIP who\_IP) (mkN "maalaama")) t)
French: By who is t ?
QPainter t = mkQS (mkQCl (mkIAdv by8agent\_Prep who\_IP) t)
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$MQuery (QPainter (PTitle TMona\_Lisa))$
Abstract syntax
SPARQL
MQuery q = "PREFIX painting:<http://spraakbanken.gu.se/rdf/owl/painting.owl#> PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#> PREFIX rdfs:<http://www.w3.org/2000/01/rdf-schema#>> SELECT distinct"++ q.wh1 ++ " WHERE { ?painting rdf:type painting:Painting; rdfs:label ?title; " ++ q.wh2 ++ q.prop++"}" ;
Concrete syntax
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Evaluation
• User satisfaction
• Efficiency in terms of time, effort and cost
• Effectiveness, how the system scales up
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Coverage: 1159 query patterns in 15 languages 10 characteristics of CH objects Extendibility New query grammar - 150 lines of code Evaluation Random queries in 7 languages with very few native informants’ corrections
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Conclusion
• NL to ontology interoperability approach
• Multilingual interface for retrieval of structured data from the Web
• Easily extendable initial base of YAQL transformations
• Great coverage of paraphrases
• Expert language/information engineers required
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Thank you for your attention
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Contacts: [email protected] [email protected] [email protected]
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