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Using WordNet to Extend FrameNet Coverage

Johansson, Richard LU and Nugues, Pierre LU orcid (2007) Building Frame Semantics Resources for Scandinavian and Baltic Languages p.27-30
Abstract
We present two methods to address the problem of sparsity in the FrameNet lexical database. The first method is based on the idea that a word that belongs to a frame is ``similar'' to the other words in that frame. We measure the similarity using a WordNet-based variant of the Lesk metric. The second method uses the sequence of synsets in WordNet hypernym trees as feature vectors that can be used to train a classifier to determine whether a word belongs to a frame or not. The extended dictionary produced by the second method was used in a system for FrameNet-based

semantic analysis and gave an improvement in recall.

We believe that the methods are useful for bootstrapping FrameNets for new languages.
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Frame semantics, natural language processing, WordNet, FrameNet
host publication
LU-CS-TR: 2007-240
editor
Nugues, Pierre and Johansson, Richard
pages
4 pages
publisher
Department of Computer Science, Lund University
conference name
Building Frame Semantics Resources for Scandinavian and Baltic Languages
conference location
Tartu, Estonia
conference dates
2007-05-24
ISBN
978-91-976939-0-5
language
English
LU publication?
yes
id
8fba37ed-1c65-4f5d-8311-2cec266dd392 (old id 630189)
date added to LUP
2016-04-04 10:58:45
date last changed
2021-05-06 17:17:01
@inproceedings{8fba37ed-1c65-4f5d-8311-2cec266dd392,
  abstract     = {{We present two methods to address the problem of sparsity in the FrameNet lexical database. The first method is based on the idea that a word that belongs to a frame is ``similar'' to the other words in that frame. We measure the similarity using a WordNet-based variant of the Lesk metric. The second method uses the sequence of synsets in WordNet hypernym trees as feature vectors that can be used to train a classifier to determine whether a word belongs to a frame or not. The extended dictionary produced by the second method was used in a system for FrameNet-based<br/><br>
semantic analysis and gave an improvement in recall.<br/><br>
We believe that the methods are useful for bootstrapping FrameNets for new languages.}},
  author       = {{Johansson, Richard and Nugues, Pierre}},
  booktitle    = {{LU-CS-TR: 2007-240}},
  editor       = {{Nugues, Pierre and Johansson, Richard}},
  isbn         = {{978-91-976939-0-5}},
  keywords     = {{Frame semantics; natural language processing; WordNet; FrameNet}},
  language     = {{eng}},
  pages        = {{27--30}},
  publisher    = {{Department of Computer Science, Lund University}},
  title        = {{Using WordNet to Extend FrameNet Coverage}},
  url          = {{https://lup.lub.lu.se/search/files/5665827/630202.pdf}},
  year         = {{2007}},
}