We present REDEN, a tool for graph-based Named Entity Linking that allows for the disambiguation of entities using domain-specific Linked Data sources and different configurations (e.g. context size). It takes TEI-annotated texts as input and outputs them enriched with external references (URIs). The possibility of customizing indexes built from various knowledge sources by defining temporal and spatial extents makes REDEN particularly suited to handle domain-specific corpora such as enriched digital editions in the Digital Humanities.

Domain-adapted named-entity linker using Linked Data

Francesca Frontini;
2015

Abstract

We present REDEN, a tool for graph-based Named Entity Linking that allows for the disambiguation of entities using domain-specific Linked Data sources and different configurations (e.g. context size). It takes TEI-annotated texts as input and outputs them enriched with external references (URIs). The possibility of customizing indexes built from various knowledge sources by defining temporal and spatial extents makes REDEN particularly suited to handle domain-specific corpora such as enriched digital editions in the Digital Humanities.
2015
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Inglese
Ruben Izquierdo
Proceedings of the Workshop on NLP Applications: Completing the Puzzle
Workshop on NLP Applications: Completing the Puzzle co-located with the 20th International Conference on Applications of Natural Language to Information Systems (NLDB 2015)
Vol-1386
10
http://ceur-ws.org/Vol-1386/named_entity.pdf
Sì, ma tipo non specificato
June 17-19, 2015
Passau, Germany
named-entity disambiguation
evaluation
linked data
digital humanities
1
none
Francesca Frontini; Carmen Brando; JeanGabriel Ganascia
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/295464
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