We present the zero-shot entity linking task, where mentions must be linked to unseen
entities without in-domain labeled data. The goal is to enable robust transfer to highly …

Supervised machine learning has several drawbacks that make it difficult to use in many
situations. Drawbacks include heavy reliance on massive training data, limited …

Abstract Information extraction from microblog posts is an important task, as today
microblogs capture an unprecedented amount of information and provide a view into the …

Recognizing names and linking them to structured data is a fundamental task in text
analysis. Existing approaches typically perform these two steps using a pipeline …

Information providers are faced with a critical challenge to process, retrieve and present
information to their users in order to satisfy their complex information needs, because data …

Social Media and consumer-generated content continue to grow and impact the hospitality
domain. Consumers write online reviews to indicate their level of satisfaction with a hotel …

Entity linking (EL), the task of disambiguating mentions in text by linking them to entities in a
knowledge graph, is crucial for text understanding, question answering or conversational …

Previous studies have highlighted the necessity for entity linking systems to capture the local
entity-mention similarities and the global topical coherence. We introduce a novel framework …

This paper considers the problem of zero-shot entity linking, in which a link in the test time
may not present in training. Following the prevailing BERT-based research efforts, we find a …

Zero-shot entity linking (EL) aims at aligning entity mentions to unseen entities to challenge
the generalization ability. Previous methods largely focus on the candidate retrieval stage …