Chatbots, conversational interfaces and NLP have achieved considerable improvements and are spreading more and more in everyday applications. Solutions on the market allow their implementation easily in different languages, but the proposals for the Italian language are not so effective as the English ones. This paper introduces ConversIAmo, the prototype of a conversational agent which implements a question answering system in Italian on a closed domain concerning artificial intelligence, taking the answers from online articles. This system integrates IBM services (Watson Assistant, Discovery and Natural Language Understanding) with functions developed within ConversIAmo and Tint, an open-source tool for the analysis of the Italian language. Our QA pipeline turned out to give better results than those obtained from using Watson Discovery service on its own, as for precision, F1-score and correct answer ranking (on average +12%, +21% and +20% respectively). Our main contribution is to address the need for an effective but easy-to-apply method aimed to improve performances of IBM Watson services for the Italian language. In addition, the AI domain is a new one for an Italian conversational agent.
ConversIAmo: Improving Italian Question Answering Exploiting IBM Watson Services
Leoni, Chiara;Torre, Ilaria;Vercelli, Gianni
2020-01-01
Abstract
Chatbots, conversational interfaces and NLP have achieved considerable improvements and are spreading more and more in everyday applications. Solutions on the market allow their implementation easily in different languages, but the proposals for the Italian language are not so effective as the English ones. This paper introduces ConversIAmo, the prototype of a conversational agent which implements a question answering system in Italian on a closed domain concerning artificial intelligence, taking the answers from online articles. This system integrates IBM services (Watson Assistant, Discovery and Natural Language Understanding) with functions developed within ConversIAmo and Tint, an open-source tool for the analysis of the Italian language. Our QA pipeline turned out to give better results than those obtained from using Watson Discovery service on its own, as for precision, F1-score and correct answer ranking (on average +12%, +21% and +20% respectively). Our main contribution is to address the need for an effective but easy-to-apply method aimed to improve performances of IBM Watson services for the Italian language. In addition, the AI domain is a new one for an Italian conversational agent.
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