Jump to content

Ann Copestake

From Wikipedia, the free encyclopedia

This is an old revision of this page, as edited by Cj005257 (talk | contribs) at 12:52, 28 July 2020 (correct hostname). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

Ann Copestake
Born
Ann Alicia Copestake
Alma mater
Scientific career
FieldsComputational linguistics[1]
Institutions
ThesisThe representation of lexical semantic information (1992)
Doctoral advisorGerald Gazdar
Websitewww.cl.cam.ac.uk/~aac10

Ann Alicia Copestake is professor of Computational Linguistics and head of the Department of Computer Science and Technology at the University of Cambridge[1][2][3][4] and a fellow of Wolfson College, Cambridge.[5]

Education

Copestake was educated at the University of Cambridge where she was awarded a Bachelor of Arts degree in Natural Sciences. After two years working for Unilever Research she completed the Cambridge Diploma in Computer Science. She went on to study at the University of Sussex where she was awarded a DPhil in 1992 for research on lexical semantics supervised by Gerald Gazdar.[6][2]

Career and research

Copestake started doing research in Natural language processing and Computational Linguistics at the University of Cambridge in 1985.[2] Since then, has been a visiting researcher at Xerox PARC (1993/4) and the University of Stuttgart (1994/5). From July 1994 to October 2000 she worked at the Center for the Study of Language and Information (CSLI) at Stanford University, as a Senior Researcher. Copestake was appointed a University Lecturer at Cambridge in October 2000.[2]

In the UK, her research has been funded by the Engineering and Physical Sciences Research Council (EPSRC) and Arts and Humanities Research Council (AHRC).[7] According to Google Scholar[1] and Scopus[3] her most cited publications include papers on minimal recursion semantics,[8] multiword expressions,[9] polysemy,[10] named-entity recognition[11] and feature structure grammars.[12]

References

  1. ^ a b c Ann Copestake publications indexed by Google Scholar
  2. ^ a b c d "Ann Copestake homepage". Cambridge: University of Cambridge. Archived from the original on 25 April 2015.
  3. ^ a b Ann Copestake's publications indexed by the Scopus bibliographic database. (subscription required)
  4. ^ "Ann Copestake – Computer Laboratory, University of Cambridge". VideoLectures.NET.
  5. ^ "Professor Ann Copestake MA DPhil, Wolfson College, Cambridge". Cambridge: University of Cambridge. Archived from the original on 17 September 2015.
  6. ^ Copestake, Ann Alicia (1992). The representation of lexical semantic information (PDF) (DPhil thesis). University of Sussex. OCLC 39162903. Archived from the original (PDF) on 29 April 2015.
  7. ^ "UK Government grants awarded to Ann Copestake". Swindon: Research Councils UK. Archived from the original on 23 November 2015.
  8. ^ Copestake, Ann; Flickinger, Dan; Pollard, Carl; Sag, Ivan A. (2005). "Minimal Recursion Semantics: An Introduction". Research on Language and Computation. 3 (2–3): 281–332. doi:10.1007/s11168-006-6327-9. ISSN 1570-7075.
  9. ^ Sag, Ivan A.; Baldwin, Timothy; Bond, Francis; Copestake, Ann; Flickinger, Dan (2002). Multiword Expressions: A Pain in the Neck for NLP. Vol. 2276. pp. 1–15. CiteSeerX 10.1.1.19.3644. doi:10.1007/3-540-45715-1_1. ISBN 978-3-540-43219-7. ISSN 0302-9743. {{cite book}}: |journal= ignored (help)
  10. ^ Copestake, Ann; Briscoe, Ted (1995). "Semi-productive Polysemy and Sense Extension". Journal of Semantics. 12 (1): 15–67. CiteSeerX 10.1.1.42.2016. doi:10.1093/jos/12.1.15. ISSN 0167-5133.
  11. ^ Corbett, Peter; Copestake, Ann (2008). "Cascaded classifiers for confidence-based chemical named entity recognition". BMC Bioinformatics. 9 (Suppl 11): S4. doi:10.1186/1471-2105-9-S11-S4. PMC 2586753. PMID 19025690.{{cite journal}}: CS1 maint: unflagged free DOI (link) Open access icon
  12. ^ Copestake, Anne (2001). Implementing Typed Feature Structure Grammars. Cambridge University Press. p. 244. ISBN 9781575862606.