Analysing biomedical text with the Stanford dependency grammar

Add to your list(s) Download to your calendar using vCal

• Andrew Clegg, Birkbeck, University of London
• Friday 19 October 2007, 12:00-13:00
• SW01 Computer Laboratory.

If you have a question about this talk, please contact Johanna Geiss.

The Stanford parser and natural language tools come with a dependency grammar and a deterministic algorithm for mapping from standard Penn Treebank-style parse trees to dependency graphs. We have shown how this provides a lingua franca for comparing various statistical parsers on biomedical text, using benchmarking methods that highlight deficiencies in their behaviour much better than tree-based analyses. We also believe dependency graphs offer a tractable intermediate step between syntax and semantics and have developed some simple approaches to information extraction based on graph traversal.

This talk is part of the NLIP Seminar Series series.

This talk is included in these lists:

• All Talks (aka the CURE list)
• Cambridge Centre for Data-Driven Discovery (C2D3)
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge talks
• Chris Davis' list
• Computer Education Research
• Computing Education Research
• Department of Computer Science and Technology talks and seminars
• Graduate-Seminars
• Guy Emerson's list
• Interested Talks
• Language Sciences for Graduate Students
• NLIP Seminar Series
• PMRFPS's
• SW01 Computer Laboratory
• Simon Baker's List
• Trust & Technology Initiative - interesting events
• bld31
• ndk22's list
• ob366-ai4er
• rp587

Note that ex-directory lists are not shown.