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Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents

Publications associées (37)

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From Web Data to Entities and Back

Zoltán Miklós, Michele Catasta, Nicolas Bonvin, Julien Gaugaz, Ekaterini Ioannou

We present the Entity Name System (ENS), an enabling infrastructure, which can host descriptions of named entities and provide unique identifiers, on large-scale. In this way, it opens new perspectives to realize entity-oriented, rather than keyword-orient ...

2010

Answering questions about archived, annotated meetings

Marita Ailomaa

Retrieving information from archived meetings is a new domain of information retrieval that has received increasing attention in the past few years. Search in spontaneous spoken conversations has been recognized as more difficult than text-based document r ...

EPFL2009

idMesh: graph-based disambiguation of linked data

Karl Aberer, Philippe Cudré-Mauroux, Parisa Haghani, Michael Jost

We tackle the problem of disambiguating entities on the Web. We propose a user-driven scheme where graphs of entities -- represented by globally identifiable declarative artifacts -- self-organize in a dynamic and probabilistic manner. Our solution has the ...

ACM2009

Natural Language Techniques for Model-driven Semantic Constraint Extraction

Martin Rajman, Marita Ailomaa

This report describes a model-driven approach to natural language understanding (NLU) in which the “meaning” of natural language queries is extracted based on a domain model composed of a set of concepts and relations specified in the system’s domain. The ...

2005

Cognitive language engineering towards robust human-computer interaction

Vincenzo Pallotta

Intelligent information processing seems to be one of the most challenging task among those involved in human-computer interaction. A central issue is how to model the various types of interaction among artificial and natural entities at different levels o ...

EPFL2002

Indexing Audio Documents by using Latent Semantic Analysis and SOM

This paper describes an important application for state-of-art automatic speech recognition, natural language processing and information retrieval systems. Methods for enhancing the indexing of spoken documents by using latent semantic analysis and self-or ...

IDIAP1999

Indexing Audio Documents by using Latent Semantic Analysis and SOM

Elsevier1999