ptlm_wsid (this link opens in a new window) by semantic-web-company (this link opens in a new window)
Usage of pre-trained language model to induce and disambiguate entity senses
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How to correctly link entities from text to your Knowledge Graph using Word Sense Induction and Disambiguation.
A quicker and more robust Word Sense Induction and Disambiguation approach for Entity Linking.
Enabling reliable disambiguation without the need to induce at all, even with incomplete sense inventories.
Type: Conference Paper
Venue: SEMANTiCS 2022
Authors: Victor Mireles, Artem Revenko, Anna Breit, Peter Bourgonje, Julián Moreno Schneider and Maria Khvalchik
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Venue: SEPLN 2022
Authors: Artem Revenko and Patricia Martín-Chozas
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Venue: SEMANTiCS
Authors: Artem Revenko, Anna Breit, Victor Mireles, Julian Moreno-Schneider, Christian Sageder, and Sotirios Karampatakis
View publicationType: Workshop Paper
Venue: DeepOntoNLP @ESWC
Authors: Patricia Martín-Chozas, Artem Revenko
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Venue: LegalAI @IEEE BigData
Authors: Anna Breit, Laura Waltersdorfer, Fajar J. Ekaputra, Marta Sabou
View publicationType: Workshop Paper
Authors: Peter Bourgonje, Anna Breit, Maria Khvalchik, Victor Mireles, Julian Moreno-Schneider, Artem Revenko, Georg Rehm
View publicationThe main objective of Lynx is to create an ecosystem of smart cloud services to better manage compliance, based on a legal knowledge graph (LKG) which integrates and links heterogeneous compliance data sources including legislation, case law, standards and other private contracts.
Visit Project WebsiteThe FFG-funded OBARIS project aims to advance the status quo in the area of auditable semantic artificial intelligence systems (SAISs), by investigating both conceptual aspects of these systems as well as a technology stack that facilitates transposing these system types into concrete settings.
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