The task of Named Entity Recognition (NER) is aimed at identifying named entities in a given text and classifying them into pre-defined domain entity types such as persons, organizations, locations. Most of the existing NER systems make use of …
**Automatic Misogyny Identification (AMI)** is a **shared task** proposed at the Evalita 2020 evaluation campaign. The AMI challenge, based on **Italian tweets**, is organized into two subtasks: (1) Subtask A about misogyny and aggressiveness …
The huge amount of textual user-generated content on the Web has incredibly grown in the last decade, creating new relevant opportunities for different real-world applications and domains. In particular, microblogging platforms enables the collection …
The paper describes the organization of the SemEval 2019 Task 5 about the detection of **hate speech against immigrants and women** in **Spanish and English** messages extracted from Twitter. The task is organized in two related classification …
**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. …
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 …
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. …