Lexical substitution is the task of identifying a substitute for a word in the context of a clause. For instance, given the following text: "After the ''match'', replace any remaining fluid deficit to prevent chronic dehydration throughout the tournament", a substitute of ''game'' might be given.
Lexical substitution is strictly related to
word sense disambiguation (WSD), in that both aim to determine the
meaning of a word. However, while WSD consists of automatically assigning the appropriate
sense
A sense is a biological system used by an organism for sensation, the process of gathering information about the world through the detection of stimuli. (For example, in the human body, the brain which is part of the central nervous system re ...
from a fixed sense inventory, lexical substitution does not impose any constraint on which substitute to choose as the best representative for the word in context. By not prescribing the inventory, lexical substitution overcomes the issue of the granularity of sense distinctions and provides a level playing field for automatic systems that automatically acquire word senses (a task referred to as
Word Sense Induction In computational linguistics, word-sense induction (WSI) or discrimination is an open problem of natural language processing, which concerns the automatic identification of the senses of a word (i.e. meanings). Given that the output of word-sense i ...
).
Evaluation
In order to evaluate automatic systems on lexical substitution, a task was organized at th
Semeval-2007evaluation competition held in
Prague
Prague ( ; cs, Praha ; german: Prag, ; la, Praga) is the capital and largest city in the Czech Republic, and the historical capital of Bohemia. On the Vltava river, Prague is home to about 1.3 million people. The city has a temperate ...
in 2007.
Semeval-2010task on cross-lingual lexical substitution has also taken place.
Skip-gram model
The skip-gram model takes words with similar meanings into a vector space (collection of objects that can be added together and multiplied by numbers) that are found close to each other in N-dimensions (list of items). A variety of
neural network
A neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus, a neural network is either a biological neural network, made up of biological ...
s (computer system modeled after a human brain) are formed together as a result of the vectors and networks that are related together. This all occurs in the dimensions of the vocabulary that has been generated in a network.
The model has been used in lexical substitution automation and prediction algorithms. One such algorithm developed by Oren Melamud, Omer Levy, and Ido Dagan uses the skip-gram model to find a vector for each word and its synonyms. Then, it calculates the cosine distance between vectors to determine which words will be the best substitutes.
Example
In a sentence like "The dog walked at a quick pace" each word has a specific vector in relation to the other. The vector for "The" would be
,0,0,0,0,0,0because the 1 is the word vocabulary and the 0s are the words surrounding that vocabulary, which create a vector.
See also
*
Lexical semantics
*
Semantic compression
*
SemEval
*
Word sense
In linguistics, a word sense is one of the meanings of a word. For example, a dictionary may have over 50 different senses of the word " play", each of these having a different meaning based on the context of the word's usage in a sentence, as ...
Bibliography
* D. McCarthy, R. Navigli
The English Lexical Substitution Task ''Language Resources and Evaluation'', 43(2), Springer, 2009, pp. 139–159.
* D. McCarthy, R. Navigli
SemEval-2007 Task 10: English Lexical Substitution Task ''Proc. of Semeval-2007 Workshop (SEMEVAL)'', in the 45th Annual Meeting of the Association for Computational Linguistics (ACL 2007), Prague, Czech Republic, 23–24 June 2007, pp. 48–53.
* D. McCarthy
Lexical substitution as a task for WSD evaluation In Proceedings of the ACL workshop on word sense disambiguation: Recent successes and future directions, Philadelphia, USA, 2002, pp. 109–115.
* R. Navigli
''Word Sense Disambiguation: A Survey', ACM Computing Surveys, 41(2), 2009, pp. 1–69.
References
Natural language processing
Computational linguistics
Lexical semantics
Semantics
Word-sense disambiguation
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