Conversational question answering (ConvQA) tackles sequential information needs where
contexts in follow-up questions are left implicit. Current ConvQA systems operate over …

Machine understanding of user utterances in conversational systems is of utmost importance
for enabling engaging and meaningful conversations with users. Entity Linking (EL) is one of …

Building conversational agents that can have natural and knowledge-grounded interactions
with humans requires understanding user utterances. Entity Linking (EL) is an effective …

Currently, named entity recognition (NER) task can be mainly divided into three types: flat,
nested, and discontinuous. In previous work, different types of NER tasks were usually …

Entity linking (EL) is a challenging task as it typically requires matching an ambiguous entity
mention with its corresponding entity in a knowledge base (KB). The mainstream studies …

There has recently been an explosion of work on spoken dialogue systems, along with an
increased interest in open-domain systems that engage in casual conversations on popular …

Named Entity Disambiguation (NED) and linking has been traditionally evaluated on natural
language content that is both well-written and contextually rich. However, many NED …

Entity linking in dialogue is the task of mapping entity mentions in utterances to a target
knowledge base. Prior work on entity linking has mainly focused on well-written articles such …

Automatic extraction of funding information from academic articles adds significant value to
industry and research communities, such as tracking research outcomes by funding …

This paper describes Radboud University's participation in the TREC Conversational
Assistance Track (CAsT) 2021 for the manually rewritten utterances. We propose an entity …