Stephen Mayhew
University of Pennsylvania
31 Papers
120 Citations
Stephen Mayhew is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Named-entity recognition & Computer science. The author has an hindex of 12, co-authored 31 publications. Previous affiliations of Stephen Mayhew include University of Illinois at Urbana–Champaign.
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Papers
•Proceedings Article
Cross-Lingual Ability of Multilingual BERT: An Empirical Study
Karthikeyan K,Zihan Wang,Stephen Mayhew,Dan Roth +3 more
- 30 Apr 2020
TL;DR: A comprehensive study of the contribution of different components in M-BERT to its cross-lingual ability, finding that the lexical overlap between languages plays a negligible role, while the depth of the network is an integral part of it.
Cheap Translation for Cross-Lingual Named Entity Recognition
Stephen Mayhew,Chen-Tse Tsai,Dan Roth +2 more
- 01 Sep 2017
TL;DR: A simple method for cross-lingual named entity recognition (NER) that works well in settings with very minimal resources, and makes use of a lexicon to “translate” annotated data available in one or several high resource language(s) into the target language, and learns a standard monolingual NER model there.
•Posted Content
Cross-Lingual Ability of Multilingual BERT: An Empirical Study
TL;DR: In this article, the authors provide a comprehensive study of the contribution of different components in multilingual BERT (M-BERT) to its cross-lingual ability and study the impact of linguistic properties of the languages, the architecture of the model, and the learning objectives.
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Cross-Lingual Named Entity Recognition via Wikification
Chen-Tse Tsai,Stephen Mayhew,Dan Roth +2 more
- 01 Aug 2016
TL;DR: A language independent method for NER is introduced, building on cross-lingual wikification, a technique that grounds words and phrases in nonEnglish text into English Wikipedia entries, yielding strong language-independent features.
MasakhaNER: Named Entity Recognition for African Languages
David Ifeoluwa Adelani,Jade Abbott,Graham Neubig,Daniel D'souza,Julia Kreutzer,Constantine Lignos,Chester Palen-Michel,Happy Buzaaba,Shruti Rijhwani,Sebastian Ruder,Stephen Mayhew,Israel Abebe Azime,Shamsuddeen Hassan Muhammad,Shamsuddeen Hassan Muhammad,Chris Chinenye Emezue,Joyce Nakatumba-Nabende,Perez Ogayo,Aremu Anuoluwapo,Catherine Gitau,Derguene Mbaye,Jesujoba O. Alabi,Seid Muhie Yimam,Tajuddeen R. Gwadabe,Ignatius Ezeani,Rubungo Andre Niyongabo,Jonathan Mukiibi,Verrah Otiende,Iroro Orife,Davis David,Samba Ngom,Tosin P. Adewumi,Paul Rayson,Mofetoluwa Adeyemi,Gerald Muriuki,Emmanuel Anebi,Chiamaka Chukwuneke,Nkiruka Odu,Eric Peter Wairagala,Samuel Oyerinde,Clemencia Siro,Tobius Saul Bateesa,Temilola Oloyede,Yvonne Wambui,Victor Akinode,Deborah Nabagereka,Maurice Katusiime,Ayodele Awokoya,Mouhamadane Mboup,Dibora Gebreyohannes,Henok Tilaye,Kelechi Nwaike,Degaga Wolde,Abdoulaye Faye,Blessing Sibanda,Orevaoghene Ahia,Bonaventure F. P. Dossou,Kelechi Ogueji,Thierno Ibrahima Diop,Abdoulaye Diallo,Adewale Akinfaderin,Tendai Marengereke,Salomey Osei +61 more
TL;DR: In this article, the authors present the first large, publicly available, high-quality dataset for named entity recognition (NER) in ten African languages and conduct an extensive empirical evaluation of state-of-the-art methods across both supervised and transfer learning settings.