no code implementations • EMNLP 2020 • Joseph Fisher, Arpit Mittal, Dave Palfrey, Christos Christodoulopoulos
It has been shown that knowledge graph embeddings encode potentially harmful social biases, such as the information that women are more likely to be nurses, and men more likely to be bankers.
1 code implementation • 19 Apr 2024 • Nacime Bouziani, Shubhi Tyagi, Joseph Fisher, Jens Lehmann, Andrea Pierleoni
Extracting structured information from unstructured text is critical for many downstream NLP applications and is traditionally achieved by closed information extraction (cIE).
Ranked #1 on Coreference Resolution on DWIE
2 code implementations • NAACL (ACL) 2022 • Tom Ayoola, Shubhi Tyagi, Joseph Fisher, Christos Christodoulopoulos, Andrea Pierleoni
The model is capable of generalising to large-scale knowledge bases such as Wikidata (which has 15 times more entities than Wikipedia) and of zero-shot entity linking.
Ranked #1 on Entity Linking on WebQSP-WD (using extra training data)
2 code implementations • NAACL 2022 • Tom Ayoola, Joseph Fisher, Andrea Pierleoni
Recent work in entity disambiguation (ED) has typically neglected structured knowledge base (KB) facts, and instead relied on a limited subset of KB information, such as entity descriptions or types.
Ranked #1 on Entity Disambiguation on ShadowLink-Top
no code implementations • 5 Dec 2019 • Joseph Fisher, Dave Palfrey, Christos Christodoulopoulos, Arpit Mittal
It has recently been shown that word embeddings encode social biases, with a harmful impact on downstream tasks.
1 code implementation • ACL 2019 • Joseph Fisher, Andreas Vlachos
Named entity recognition (NER) is one of the best studied tasks in natural language processing.
Ranked #4 on Nested Mention Recognition on ACE 2005