International audienceThis article presents an overview of approaches and results during our participation in the CLEF HIPE 2020 NERC-COARSE-LIT and EL-ONLY tasks for English and French. For these two tasks, we use two systems: 1) DeLFT, a Deep Learning framework for text processing; 2) entity-fishing, generic named entity recognition and disambiguation service deployed in the technical framework of INRIA
HIPE is a named entity processing evaluation campaign on historical newspapers in French, German and...
Due to COVID19 pandemic, the 12th edition is cancelled. The LREC 2020 Proceedings are available at h...
We present the HIPE-2022 shared task on named entity processing in multilingual historical documents...
This paper presents an extended overview of the first edition of HIPE (Identifying Historical People...
International audienceIn this article we present the approaches developed by the Sorbonne-INRIA for ...
International audienceThis paper summarizes the participation of the L3i laboratory of the Universit...
CLEF-HIPE-2020 (Identifying Historical People, Places and other Entities) is a evaluation campaign o...
Since its introduction some twenty years ago, named entity (NE) processing has become an essential c...
This paper presents an overview of the first edition of HIPE (Identifying Historical People, Places ...
Contains fulltext : 233830.pdf (Publisher’s version ) (Open Access)CLEF 202
International audienceThis note describes IRISA's system for the task of named entity processing on ...
This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places...
International audienceThis paper describes the participation of master's students (LITL programme, u...
International audienceThis paper presents an attempt to provide a generic named-entity recognition a...
HIPE is a named entity processing evaluation campaign on historical newspapers in French, German and...
Due to COVID19 pandemic, the 12th edition is cancelled. The LREC 2020 Proceedings are available at h...
We present the HIPE-2022 shared task on named entity processing in multilingual historical documents...
This paper presents an extended overview of the first edition of HIPE (Identifying Historical People...
International audienceIn this article we present the approaches developed by the Sorbonne-INRIA for ...
International audienceThis paper summarizes the participation of the L3i laboratory of the Universit...
CLEF-HIPE-2020 (Identifying Historical People, Places and other Entities) is a evaluation campaign o...
Since its introduction some twenty years ago, named entity (NE) processing has become an essential c...
This paper presents an overview of the first edition of HIPE (Identifying Historical People, Places ...
Contains fulltext : 233830.pdf (Publisher’s version ) (Open Access)CLEF 202
International audienceThis note describes IRISA's system for the task of named entity processing on ...
This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places...
International audienceThis paper describes the participation of master's students (LITL programme, u...
International audienceThis paper presents an attempt to provide a generic named-entity recognition a...
HIPE is a named entity processing evaluation campaign on historical newspapers in French, German and...
Due to COVID19 pandemic, the 12th edition is cancelled. The LREC 2020 Proceedings are available at h...
We present the HIPE-2022 shared task on named entity processing in multilingual historical documents...