Tweet2Check evaluation at Evalita Sentipolc 2016

Rosa, Emanuele Di; Durante, Alberto

doi:10.4000/books.aaccademia.2012

Cited by 3 publications

(1 citation statement)

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“…which attracted 12 submissions from 7 teams. The highest F-score was achieved by tweet2check at 0.5412 (constrained run) (Di Rosa and Durante 2016). The only unconstrained run was submitted by Unitor achieving 0.4810 as F-score.…”

Section: Participating Systems and Resultsmentioning

confidence: 99%

EVALITA Goes Social: Tasks, Data, and Community at the 2016 Edition

Basile¹,

Patti²,

Cutugno³

et al. 2017

ijcol

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EVALITA, the evaluation campaign of Natural Language Processing and Speech Tools for the Italian language, was organised for the fifth time in 2016. Six tasks, covering both re-reruns as well as completely new tasks, and an IBM-sponsored challenge, attracted a total of 34 submissions. An innovative aspect at this edition was the focus on social media data, especially Twitter, and the use of shared data across tasks, yielding a test set with layers of annotation concerning PoS tags, sentiment information, named entities and linking, and factuality information. Differently from the previous edition(s), many systems relied on a neural architecture, and achieved best results when used. From the experience and success of this edition, also in terms of dissemination of information and data, and in terms of collaboration between organisers of different tasks, we collected some reflections and suggestions that prospective EVALITA chairs might be willing to take into account for future editions.

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Section: Participating Systems and Resultsmentioning

confidence: 99%