creators_name: Mayberry, Marshall R
creators_name: Miikkulainen, Risto
type: confpaper
datestamp: 2002-12-11
lastmod: 2011-03-11 08:55:07
metadata_visibility: show
title:  Lexical Disambiguation Based on Distributed Representations of Context Frequency
ispublished: pub
subjects: comp-sci-lang
subjects: comp-sci-neural-nets
subjects: comp-sci-art-intel
full_text_status: public
keywords: "lexical disambiguation" "neural networks" "multiple-access"
abstract: A model for lexical disambiguation is presented that is based on combining the frequencies of past contexts of ambiguous words. The frequencies are encoded in the word representations and define the words' semantics. A Simple Recurrent Network (SRN) parser combines the context frequencies one word at a time, always producing the most likely interpretation of the current sentence at its output. This disambiguation process is most striking when the interpretation involves semantic flipping, that is, an alternation between two opposing meanings as more words are read in. The sense of ``throwing a ball'' alternates between ``dance'' and ``baseball'' as indicators such as the agent, location, and recipient are input. The SRN parser      demonstrates how the context frequencies are dynamically combined to determine the interpretation of such sentences. We hypothesize that several other aspects of ambiguity resolution are based on similar mechanisms, and can be naturally approached from the distributed connectionist viewpoint. 
date: 1994
date_type: published
publisher: Hillsdale, NJ: Erlbaum, 1994.
pagerange: 601-606
refereed: TRUE
citation:   Mayberry, Marshall R and Miikkulainen, Dr. Risto  (1994)  Lexical Disambiguation Based on Distributed Representations of Context Frequency.  [Conference Paper]     
document_url: http://cogprints.org/2645/1/mayberry.disambiguation.pdf