CORVIDAE: Coreference resolution visual development & analysis environment

Autor(en): Möller, N.
Heidemann, G. 
Herausgeber: Folmer, E.
Cuquet, M.
Martin, M.
Stichwörter: Semantics, Co-reference resolutions; Global knowledge; Human level intelligence; Language understanding; NAtural language processing; Time progress; Visual development; World knowledge, Natural language processing systems
Erscheinungsdatum: 2016
Herausgeber: CEUR-WS
Journal: CEUR Workshop Proceedings
Volumen: 1695
Zusammenfassung: 
Communication whether in verbal or written form is part of our daily life. Hence, we as humans have developed a set of skills that enable us to follow a discourse and extract important information from a text quite easily. For a machine, however language understanding is a quite challenging problem and considered to be AI-complete, i.e. a machine must reach human level intelligence in order to solve this task. Recent developments, especially those forming the semantic web, offer new ways of incorporating world knowledge into natural language processing methods, while at the same time progress made in the latter will help pushing the dream of the global knowledge graph closer to reality. In this paper we present CORVIDAE (Coreference Resolution Visual Development & Analysis Environment) a tool for NLP developers to analyse and eventually improve coreference resolution algorithms specially designed for those that interact with world knowledge. © 2016 Copyright held by the author/owner(s).s).
Beschreibung: 
Conference of 12th Joint International Conference on Semantic Systems, SEMANTiCS 2016 and the 1st International Workshop on Semantic Change and Evolving Semantics, SuCCESS 2016 ; Conference Date: 12 September 2016 Through 15 September 2016; Conference Code:124177
ISSN: 16130073
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84992348120&partnerID=40&md5=e9555fbb10ed8349d1ae986cd11ce49b

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