After decades of massive digitisation, an unprecedented number of historical documents are
available in digital format, along with their machine-readable texts. While this represents a …

Natural-language prompts have recently been used to coax pretrained language models
into performing other AI tasks, using a fill-in-the-blank paradigm (Petroni et al., 2019) or a …

This paper presents an extended overview of the first edition of HIPE (Identifying Historical
People, Places and other Entities), a pioneering shared task dedicated to the evaluation of …

Abstract Knowledge graph (KG) is known to be helpful for the task of question answering
(QA), since it provides well-structured relational information between entities, and allows …

This survey presents a comprehensive description of recent neural entity linking (EL)
systems developed since 2015 as a result of the “deep learning revolution” in natural …

Abstract Entity Linking (EL) and Word Sense Disambiguation (WSD) both address the lexical
ambiguity of language. But while the two tasks are pretty similar, they differ in a fundamental …

Applying natural language processing for mining and intelligent information access to tweets
(a form of microblog) is a challenging, emerging research area. Unlike carefully authored …

In this paper we present the Multilingual All-Words Sense Disambiguation and Entity Linking
task. Word Sense Disambiguation (WSD) and Entity Linking (EL) are well-known problems …

In sequential recommendation, multi-modal information (eg, text or image) can provide a
more comprehensive view of an item's profile. The optimal stage (early or late) to fuse …

The past decade has witnessed the emergence of several publicly available and proprietary
knowledge graphs (KGs). The depth and breadth of content in these KGs made them not …