nlp

Overview of the Evalita 2018 Task on Automatic Misogyny Identification (AMI)

**Automatic Misogyny Identification** (AMI) is a new **shared task** proposed for the first time at the Evalita 2018 evaluation campaign. The AMI challenge, based on both **Italian and English** tweets, is distinguished into two subtasks, i.e. …

Mapping Natural Language Labels to Structured Web Resources

Mapping natural language terms to a Web knowledge base enriches information systems without additional context, with new relations and properties from the Linked Open Data. In this paper we formally define such task, which is related to word sense …

Towards encoding time in text-based entity embeddings

Knowledge Graphs (KG) are widely used abstractions to represent entity-centric knowledge. Approaches to embed entities, entity types and relations represented in the graph into vector spaces - often referred to as KG embeddings - have become …

UNIMIB@ NEEL-IT: Named Entity Recognition and Linking of Italian Tweets

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 …

Adapting Named Entity Types to New Ontologies in a Microblogging Environment

Given the potential rise in the amount of user-generated content on social network, research efforts towards Information Extraction have significantly increased, giving leeway to the emergence of numerous *Named Entity Recognition* (NER) systems. …

A Multi-View Sentiment Corpus

Sentiment Analysis is a broad task that involves the analysis of various aspect of the natural language text. However, most of the approaches in the state of the art usually investigate independently each aspect, i.e. Subjectivity Classification, …

Towards adaptation of named entity classification

Numerous state-of-the-art **Named Entity Recognition** (NER) systems use different classification schemas/ontologies. Comparisons and integration among NER systems, thus, becomes complex. In this paper, we propose a transfer-learning approach where …