no code implementations • 24 May 2023 • Jeremy R. Cole, Michael J. Q. Zhang, Daniel Gillick, Julian Martin Eisenschlos, Bhuwan Dhingra, Jacob Eisenstein
We investigate question answering from this perspective, focusing on answering a subset of questions with a high degree of accuracy, from a set of questions in which many are inherently ambiguous.
no code implementations • 23 May 2023 • Livio Baldini Soares, Daniel Gillick, Jeremy R. Cole, Tom Kwiatkowski
Neural document rerankers are extremely effective in terms of accuracy.
no code implementations • 29 Jun 2021 • Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, Daniel Gillick, Jacob Eisenstein, William W. Cohen
We introduce a diagnostic dataset aimed at probing LMs for factual knowledge that changes over time and highlight problems with LMs at either end of the spectrum -- those trained on specific slices of temporal data, as well as those trained on a wide range of temporal data.
no code implementations • ACL 2021 • Nicholas FitzGerald, Jan A. Botha, Daniel Gillick, Daniel M. Bikel, Tom Kwiatkowski, Andrew McCallum
We present an instance-based nearest neighbor approach to entity linking.
1 code implementation • EMNLP 2020 • Jan A. Botha, Zifei Shan, Daniel Gillick
We propose a new formulation for multilingual entity linking, where language-specific mentions resolve to a language-agnostic Knowledge Base.
Ranked #1 on Entity Disambiguation on Mewsli-9 (using extra training data)
no code implementations • CONLL 2019 • Daniel Gillick, Sayali Kulkarni, Larry Lansing, Alessandro Presta, Jason Baldridge, Eugene Ie, Diego Garcia-Olano
We show that it is feasible to perform entity linking by training a dual encoder (two-tower) model that encodes mentions and entities in the same dense vector space, where candidate entities are retrieved by approximate nearest neighbor search.
no code implementations • 19 Nov 2018 • Daniel Gillick, Alessandro Presta, Gaurav Singh Tomar
Most text-based information retrieval (IR) systems index objects by words or phrases.
no code implementations • EMNLP 2018 • Yuan Zhang, Jason Riesa, Daniel Gillick, Anton Bakalov, Jason Baldridge, David Weiss
We address fine-grained multilingual language identification: providing a language code for every token in a sentence, including codemixed text containing multiple languages.