This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering by using a graph-based approach.
Cecchini, F., Fersini, E., Manchanda, P., Messina, V., Nozza, D., Palmonari, M., et al. (2016). UNIMIB@NEEL-IT : Named entity recognition and linking of Italian tweets. In In Proc. of the 3rd Italian Conference on Computational Linguistics CLiC-it 2016. CEUR-WS [10.4000/books.aaccademia.1938].
UNIMIB@NEEL-IT : Named entity recognition and linking of Italian tweets
Cecchini, F;Fersini, E;Manchanda, P;Messina, V;Nozza, D;Palmonari, M;
2016
Abstract
This paper describes the framework proposed by the UNIMIB Team for the task of Named Entity Recognition and Linking of Italian tweets (NEEL-IT). The proposed pipeline, which represents an entry level system, is composed of three main steps: (1) Named Entity Recognition using Conditional Random Fields, (2) Named Entity Linking by considering both Supervised and Neural-Network Language models, and (3) NIL clustering by using a graph-based approach.
| File | Dimensione | Formato | |
|---|---|---|---|
|
10281-135614.pdf
accesso aperto
Tipologia di allegato:
Publisher’s Version (Version of Record, VoR)
Dimensione
8.35 MB
Formato
Adobe PDF
|
8.35 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
