Abstract
The JDM lexical network has been built thanks to on-line games the main of which, JeuxDeMots (JDM), was launched in 2007. It is currently a large lexical network, in constant evolution, containing more than 310,000 terms connected by more than 6.5 million relations. The riddle game Totaki (Tip Of the Tongue with Automated Knowledge Inferences), the initial version of which was elaborated with Michael Zock, was launched in a first version in 2010. The initial aim of this project is to cross validate the JDM lexical network. Totaki uses this lexical network to make proposals from user given clues, and in case of failure players can supply new information, hence enriching the network. Endogenous processes of inference, by deduction, induction, abduction, also allow to find new information not directly available in the network and hence lead to a densification of the network. The assumption about the validation is that if Totaki is able to guess proper terms from user clues, then the lexical network contains appropriate relations between words. Currently, Totaki achieves a 75 % success rate, to be compared to less than 50 % if the guessing is done by human users. One serious application of Totaki is to be viewed as a tool for lexical access and a possible remedy for the tip of the tongue problem. The Wikipedia encyclopaedia, built in a collaborative way, represents a very important volume of knowledge (about 1.5 million articles in its French version). The idea developed in this chapter consists in benefiting from Wikipedia to enrich the JDM network and evaluate the impact on Totaki performance. Instead of relying only on the JDM network, Totaki also makes use of information extracted from Wikipedia. The overall process is then both endogenous and exogenous. In a first part, we shall remind the reader the basic principles of a lexical network, then the aims and the underlying principles of the Totaki game. We shall see on examples Totaki may be used as a game to evaluate and enrich the JDM network, but also it may be considered as a tool for the Tip Of the Tongue problem; partial syntactic or morphologic information may be added to semantic information to help the user. In a second part, we shall show the results of the evaluation of the JDM network, results we obtained playing Totaki. We shall clarify the process allowing the introduction in the Totaki game of data extracted from Wikipedia as a complement in the information from the JDM network, and we shall briefly present the results provided by the first experiments.
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Notes
- 1.
In particular, new terms (e.g.: obamania or to vapote) or new meanings of already existing terms (e.g.: tablet) regularly arise.
- 2.
Here, it is about relations acquired thanks to JDM game. The main part of the other relations present in the network was acquired by deduction, induction, abduction processes (about 1 million relations) or using data from Wikipedia (about 3.5 million relations).
- 3.
e.g.: magn (fever) = high fever.
- 4.
e.g.: scissors → cut.
- 5.
The TOT problem has been studied by a lot of authors. One of the most recent analysis (Zock and Schwab 2013) also supplies very promising elements of answer.
- 6.
Years (e.g.: 1984) are not taken into account; on the other hand, dates (e.g.: September 11th) are.
References
Carlson, A., Betteridge, J., Kisiel, B., Settles, B., Hruschka, E. R., & Mitchell, T. M. (2010). Toward an architecture for never-ending language learning. In Proceedings of the Conference on Artificial Intelligence (AAAI), (p. 8).
Collins, A., & Quillian, M. R. (1969). Retrieval time from semantic memory. Journal of Verbal Learning and Verbal Behaviour, 8(2), 240–248.
Ferrucci, D., Brown, E., Chu-Carroll, J., Fan, J., Gondek, D., Kalyanpur, A., et al. (2010). Building watson: An overview of the DeepQA project. AI Magazine, 31(3), 59–79.
Joubert, A., & Lafourcade, M. (2012). A new dynamic approach for lexical networks evaluation. In Proceedings of the 8 th edition of Language Resources and Evaluation Conference (LREC 2012), (p. 5). Istanbul: ELRA.
Lafourcade, M. (2007). Making people play for lexical acquisition. In Proceedings of the 7th Symposium on Natural Language Processing (SNLP 2007), (p. 8). December 13–15, 2007, Pattaya, Thaïland.
Lafourcade, M., Joubert, A., Schwab, D., et Zock, M. (2011). Évaluation et consolidation d’un réseau lexical grâce à un assistant ludique pour le “mot sur le bout de la langue”. In Proceedings of TALN’11, (pp. 295–306). Montpellier, France, 27 juin-1er juillet 2011.
Lafourcade, M., & Joubert, A. (2013). Bénéfices et limites de l’acquisition lexicale dans l’expérience JeuxDeMots. In N. Gala & M. Zock (Eds.), Ressources lexicales (pp. 187–216), John Benjamins Publishing, Amsterdam.
Mel’čuk, I. A., Clas, A., & Polguère, A. (1995). Introduction à la lexicologie explicative et combinatoire. Louvain-la-Neuve: Duculot AUPELF-UREF.
Polguère, A. (2006). Structural properties of lexical systems: monolingual and multilingual perspectives. In Workshop on Multilingual Language Resources and Interoperability (COLING/ACL 2006), (pp. 50–59). Sydney.
Zarrouk, M., Lafourcade, M., & Joubert, A. (2013). Inductive and deductive inferences in a crowdsourced lexical-semantic network. In proceedings of the 9th International Conference on Recent Advances in Natural Language Processing (RANLP 2013), (p. 6). September 7–13, 2013, Hissar, Bulgaria.
Zock, M., & Schwab, D. (2013). L’index, une ressource vitale pour guider les auteurs à trouver le mot bloqué sur le bout de la langue. In N. Gala & M. Zock (Eds.) Ressources lexicales (pp. 313–354), John Benjamins Publishing, Amsterdam.
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Lafourcade, M., Joubert, A. (2015). TOTAKI: A Help for Lexical Access on the TOT Problem. In: Gala, N., Rapp, R., Bel-Enguix, G. (eds) Language Production, Cognition, and the Lexicon. Text, Speech and Language Technology, vol 48. Springer, Cham. https://doi.org/10.1007/978-3-319-08043-7_7
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