International audienceThis note describes IRISA's system for the task of named entity processing on historical newspapers in French. Following a standard entity detection and linking pipeline, our system implements three steps to solve the named entity linking task. Named Entity Recognition (NER) is first performed to identify the entity mentions in a document based on a Conditional Random Fields classifier. Candidate entities from Wikidata are then generated for each mention found, using simple search. Finally, every mention is linked to one of its candidate entities in a so-called linking step leveraging various string metrics and the semantic structure of Wikidata to improve on the linking decisions
Named entities (NEs) are among the most relevant type of information that can be used to efficiently...
CLEF-HIPE-2020 (Identifying Historical People, Places and other Entities) is a evaluation campaign o...
This thesis proposes new methods for entity linking in natural language text that assigns entity men...
International audienceThis note describes IRISA's system for the task of named entity processing on ...
Contains fulltext : 233830.pdf (Publisher’s version ) (Open Access)CLEF 202
International audienceWe present a joint system for named entity recognition (NER) and entity linkin...
International audienceThis paper summarizes the participation of the L3i laboratory of the Universit...
Since its introduction some twenty years ago, named entity (NE) processing has become an essential c...
International audienceIn this article we present the approaches developed by the Sorbonne-INRIA for ...
This paper presents an extended overview of the first edition of HIPE (Identifying Historical People...
This paper presents an overview of the first edition of HIPE (Identifying Historical People, Places ...
International audienceIn the applicative context of news wire enrichment with metadata, named entity...
International audienceThis article presents an overview of approaches and results during our partici...
HIPE is a named entity processing evaluation campaign on historical newspapers in French, German and...
This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places...
Named entities (NEs) are among the most relevant type of information that can be used to efficiently...
CLEF-HIPE-2020 (Identifying Historical People, Places and other Entities) is a evaluation campaign o...
This thesis proposes new methods for entity linking in natural language text that assigns entity men...
International audienceThis note describes IRISA's system for the task of named entity processing on ...
Contains fulltext : 233830.pdf (Publisher’s version ) (Open Access)CLEF 202
International audienceWe present a joint system for named entity recognition (NER) and entity linkin...
International audienceThis paper summarizes the participation of the L3i laboratory of the Universit...
Since its introduction some twenty years ago, named entity (NE) processing has become an essential c...
International audienceIn this article we present the approaches developed by the Sorbonne-INRIA for ...
This paper presents an extended overview of the first edition of HIPE (Identifying Historical People...
This paper presents an overview of the first edition of HIPE (Identifying Historical People, Places ...
International audienceIn the applicative context of news wire enrichment with metadata, named entity...
International audienceThis article presents an overview of approaches and results during our partici...
HIPE is a named entity processing evaluation campaign on historical newspapers in French, German and...
This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places...
Named entities (NEs) are among the most relevant type of information that can be used to efficiently...
CLEF-HIPE-2020 (Identifying Historical People, Places and other Entities) is a evaluation campaign o...
This thesis proposes new methods for entity linking in natural language text that assigns entity men...