Year: 2014
Type: conference-paper
Abstract: This paper presents our system for the "Making Sense of Microposts 2014 (#Microposts2014)" challenge.Our system is based on AIDA, an existing system that links entity mentions in natural language text to their corresponding canonical entities in a knowledge base (KB).AIDA collectively exploits the prominence of entities, contextual similarities, and coherence to effectively disambiguate entity mentions.The system was originally developed for clean and well-structured text (e. g. news articles).We adapt it for microposts, specifically tweets, with special focus on the named entity recognition and the entity candidate lookup.
Source: MPG.PuRe (Max Planck Society)
Institutions: Max Planck Society, Max Planck Institute for Informatics
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W636489255