In this paper we present the MicroNeel system for Named Entity Recognition and Entity Linking on Italian microposts, which participated in the NEELIT task at EVALITA 2016. MicroNeel combines The Wiki Machine and Tint, two standard NLP tools, with comprehensive tweet preprocessing, the Twitter- DBpedia alignments from the Social Media Toolkit resource, and rule-based or supervised merging of produced annotations.

MicroNeel: Combining NLP Tools to Perform Named Entity Detection and Linking on Microposts / Corcoglioniti, Francesco; Palmero Aprosio, Alessio; Nechaev, Yaroslav; Giuliano, Claudio. - 1749:(2016). (Intervento presentato al convegno CLiC-it & EVALITA 2016 tenutosi a Napoli, Italia nel 5th-7th December 2016).

MicroNeel: Combining NLP Tools to Perform Named Entity Detection and Linking on Microposts

Corcoglioniti, Francesco;Palmero Aprosio, Alessio;Nechaev, Yaroslav;
2016-01-01

Abstract

In this paper we present the MicroNeel system for Named Entity Recognition and Entity Linking on Italian microposts, which participated in the NEELIT task at EVALITA 2016. MicroNeel combines The Wiki Machine and Tint, two standard NLP tools, with comprehensive tweet preprocessing, the Twitter- DBpedia alignments from the Social Media Toolkit resource, and rule-based or supervised merging of produced annotations.
2016
Proceedings of Third Italian Conference on Computational Linguistics (CLiC-it 2016) & Fifth Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2016)
Napoli, Italia
CEUR
Corcoglioniti, Francesco; Palmero Aprosio, Alessio; Nechaev, Yaroslav; Giuliano, Claudio
MicroNeel: Combining NLP Tools to Perform Named Entity Detection and Linking on Microposts / Corcoglioniti, Francesco; Palmero Aprosio, Alessio; Nechaev, Yaroslav; Giuliano, Claudio. - 1749:(2016). (Intervento presentato al convegno CLiC-it & EVALITA 2016 tenutosi a Napoli, Italia nel 5th-7th December 2016).
File in questo prodotto:
File Dimensione Formato  
paper_010 (1).pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 521.95 kB
Formato Adobe PDF
521.95 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/413064
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
  • OpenAlex ND
social impact