9 research outputs found
Exploiting Multiword Expressions to Solve âLa Ghigliottinaâ
Il contributo descrive il sistema UNIOR4NLP, sviluppato per risolvere il gioco âLa Ghigliottinaâ, che ha partecipato alla sfida NLP4FUN della campagna di valutazione Evalita 2018. Il sistema risulta il migliore della competizione e ha prestazioni piĂč elevate rispetto agli umani.The paper describes UNIOR4NLP a system developed to solve âLa Ghigliottinaâ game which took part in the NLP4FUN task of the Evalita
2018 evaluation campaign. The system is the best performing one in the competition and achieves better results than human players
âIl Mago della Ghigliottinaâ @ Ghigliottin-AI: When Linguistics meets Artificial Intelligence
This paper describes Il mago della Ghigliottina, a bot which took part in the Ghigliottin-AI task of the Evalita 2020 evaluation campaign. The aim is to build a system able to solve the TV game âLa Ghigliottinaâ. Our system has already participated in the Evalita 2018 task NLP4FUN. Compared to that occasion, it improved its accuracy from 61% to 68.6%.Questo contributo descrive Il mago della Ghigliottina, un bot che ha partecipato a Ghigliottin-AI, uno dei task di Evalita 2020. Scopo del task Ăš mettere in piedi un sistema automatico capace di risolvere il gioco televisivo âLa Ghigliottinaâ. Il nostro sistema ha giĂ partecipato allâedizione del 2018 di Evalita al task NLP4FUN. Rispetto allâedizione del 2018 di NLP4FUN, lâaccuratezza Ăš salita dal 61% al 68.6%
Ghigliottin-AI @ EVALITA2020: Evaluating Artificial Players for the Language Game âLa Ghigliottinaâ
Evaluating Artificial Players for the Language Game âLa Ghigliottinaâ (Ghigliottin-AI) task is one of the tasks organized in the context of the 2020 EVALITA edition, a periodic evaluation campaign of Natural Language Processing (NLP) and speech tools for the Italian language. Ghigliottin-AI participants are asked to build an artificial player able to solve âLa Ghigliottinaâ, namely the final game of an Italian TV show called âLâEreditĂ â. The game involves a single player who is given a set of five words unrelated to each other, but related with a sixth word that represents the solution to the game. Fourteen teams registered to Ghigliottin-AI. Nevertheless, only two teams submitted their run. In order to evaluate the submitted systems, we rely on an API base methodology, via a Remote Evaluation Server (RES). In this report we describe the Ghigliottin-AI task, the data, the evaluation and we discuss results
Lessons Learned from EVALITA 2020 and Thirteen Years of Evaluation of Italian Language Technology
This paper provides a summary of the 7th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian (EVALITA2020) which was held online on December 17th, due to the 2020 COVID-19 pandemic. The 2020 edition of Evalita included 14 different tasks belonging to five research areas, namely: (i) Affect, Hate, and Stance, (ii) Creativity and Style, (iii) New Challenges in Long-standing Tasks, (iv) Semantics and Multimodality, (v) Time and Diachrony. This paper provides a description of the tasks and the key findings from the analysis of participant outcomes. Moreover, it provides a detailed analysis of the participants and task organizers which demonstrates the growing interest with respect to this campaign. Finally, a detailed analysis of the evaluation of tasks across the past seven editions is provided; this allows to assess how the research carried out by the Italian community dealing with Computational Linguistics has evolved in terms of popular tasks and paradigms during the last 13 years
Ghigliottin-AI @ EVALITA2020: Evaluating artificial players for the language game âLa Ghigliottinaâ
Evaluating Artificial Players for the Language Game âLa Ghigliottinaâ (Ghigliottin-AI) task is one of the tasks organized in the context of the 2020 EVALITA edition, a periodic evaluation campaign of Natural Language Processing (NLP) and speech tools for the Italian language. Ghigliottin-AI participants are asked to build an artificial player able to solve âLa Ghigliottinaâ, namely the final game of an Italian TV show called âL'EreditĂ â. The game involves a single player who is given a set of five words unrelated to each other, but related with a sixth word that represents the solution to the game. Fourteen teams registered to Ghigliottin-AI. Nevertheless, only two teams submitted their run. In order to evaluate the submitted systems, we rely on an API base methodology, via a Remote Evaluation Server (RES). In this report we describe the Ghigliottin-AI task, the data, the evaluation and we discuss results
EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020
Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)
EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020
Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)
Overview of the EVALITA 2018 Solving language games (NLP4FUN) Task
This paper describes the first edition of the âSolving language gamesâ (NLP4FUN) task at the EVALITA 2018 campaign. The task consists in designing an artificial player for âThe Guillotineâ (La Ghigliottina, in Italian), a challenging language game which demands knowledge covering a broad range of topics. The game consists in finding a word which is semantically correlated with a set of 5 words called clues. Artificial players for that game can take advantage from the availability of open repositories on the web, such as Wikipedia, that provide the system with the cultural and linguistic background needed to find the solution