0000000000178643

AUTHOR

Uldis Lavrinovics

showing 3 related works from this author

Pini Language and PiniTree Ontology Editor: Annotation and Verbalisation for Atomised Journalism

2020

We present a new ontology language Pini and the PiniTree ontology editor supporting it. Despite Pini language bearing lot of similarities with RDF, UML class diagrams, Property Graphs and their frontends like Google Knowledge Graph and Protege, it is a more expressive language enabling FrameNet-style natural language annotation for Atomised journalism use case.

Computer science05 social sciences050801 communication & media studies02 engineering and technologycomputer.file_formatOntology languageProtégéLinguisticsAnnotation0508 media and communicationsUnified Modeling Language0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingJournalismClass diagramRDFcomputerNatural languagecomputer.programming_language
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LinkedSaeima: A Linked Open Dataset of Latvia’s Parliamentary Debates

2019

This paper describes the LinkedSaeima dataset that contains structured data about Latvia’s parliamentary debates from 1993 until 2017. This information is published at http://dati.saeima.korpuss.lv as Linked Open Data. It is a part of the Corpus of Saeima (the Parliament of Latvia) released as open data for multidisciplinary research. The data model of LinkedSaeima follows the data structure of the LinkedEP dataset with a few modifications. The dataset is augmented with links to the Wikidata knowledge base that provide additional information about the speakers and named entities mentioned in the corpus.

Thesaurus (information retrieval)business.industryParliamentComputer sciencemedia_common.quotation_subject05 social sciences02 engineering and technologycomputer.file_formatLinked dataData structureWorld Wide WebOpen dataData modelKnowledge base020204 information systems0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesRDFbusinesscomputer050104 developmental & child psychologymedia_common
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RDF* Graph Database as Interlingua for the TextWorld Challenge

2019

This paper briefly describes the top-scoring submission to the First TextWorld Problems: A Reinforcement and Language Learning Challenge. To alleviate the partial observability problem, characteristic to the TextWorld games, we split the Agent into two independent components: Observer and Actor, communicating only via the Interlingua of the RDF* graph database. The RDF* graph database serves as the “world model” memory incrementally updated by the Observer via FrameNet informed Natural Language Understanding techniques and is used by the Actor for the efficient exploration and planning of the game Action sequences. We find that the deep-learning approach works best for the Observer componen…

InterlinguaInformation retrievalGraph databaseComputer scienceBacktrackingbusiness.industryDeep learningNatural language understandingcomputer.file_formatcomputer.software_genrelanguage.human_languagelanguageReinforcement learningArtificial intelligenceRDFFrameNetbusinesscomputer2019 IEEE Conference on Games (CoG)
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