Named Entity Recognition and Linking in Tweets Based on Linguistic Similarity
This work proposes a novel approach in Named Entity rEcognition and Linking (NEEL) in tweets, applying the same strategy already presented for Question Answering (QA) by the same authors. The previous work describes a rule-based and ontology-based system that attempts to retrieve the correct answer to a query from the DBPedia ontology through a similarity measure between the query and the ontology labels. In this paper, a tweet is interpreted as a query for the QA system: both the text and the thread of a tweet are a sequence of statements that have been linked to the ontology. Provided that tweets make extensive use of informal language, the similarity measure and the underlying processes …
ChiLab4It system in the QA4FAQ competition
ChiLab4It is the Question Answering system (QA) for Frequently Asked Questions (FAQ) developed by the Computer-Human Interaction Laboratory (ChiLab) at the University of Palermo for participating to the QA4FAQ task at EVALITA 2016 competition. The system is the versioning of the QuASIt framework developed by the same authors, which has been customized to address the particular task. This technical report describes the strategies that have been imported from QuASIt for implementing ChiLab4It, the actual system implementation, and the comparative evaluations with the results of the other participant tools, as provided by the organizers of the task. ChiLab4It was the only system whose score re…
QuASIt: A Cognitive Inspired Approach to Question Answering for the Italian Language
In this paper we present QuASIt, a Question Answering System for the Italian language, and the underlying cognitive architecture. The term cognitive is meant in the procedural semantics perspective, which states that the interpretation and/or production of a sentence requires the execution of some cognitive processes over both a perceptually grounded model of the world, and a linguistic knowledge acquired previously. We attempted to model these cognitive processes with the aim to make an artificial agent able both to understand and produce natural language sentences. The agent runs these processes on its inner domain representation using the linguistic knowledge also. In this sense, QuASIt …