- Title
- Theoretical study and empirical investigation of sentence analogies
- Creator
- Afantenos, Stergos; Lim, Suryani; Prade, Henri; Richard, Gilles
- Date
- 2022
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/190497
- Identifier
- vital:17613
- Identifier
- ISBN:1613-0073 (ISSN)
- Abstract
- Analogies between 4 sentences, “a is to b as c is to d”, are usually defined between two pairs of sentences (a, b) and (c, d) by constraining a relation R holding between the sentences of the first pair, to hold for the second pair. From a theoretical perspective, three postulates define an analogy - one of which is the “central permutation” postulate which allows the permutation of central elements b and c. This postulate is no longer appropriate in sentence analogies since the existence of R offers no guarantee in general for the existence of some relation S such that S also holds for the pairs (a, c) and (b, d). In this paper, the “central permutation” postulate is replaced by a weaker “internal reversal” postulate to provide an appropriate definition of sentence analogies. To empirically validate the aforementioned postulate, we build a LSTM as well as baseline Random Forest models capable of learning analogies based on quadruplets. We use the Penn Discourse Treebank (PDTB), the Stanford Natural Language Inference (SNLI) and the Microsoft Research Paraphrase (MSRP) corpora. Our experiments show that our models trained on samples of analogies between (a, b) and (c, d), recognize analogies between (b, a) and (d, c) when the underlying relation is symmetrical, validating thus the formal model of sentence analogies using “internal reversal” postulate. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
- Publisher
- CEUR-WS
- Relation
- 1st Workshop on the Interactions between Analogical Reasoning and Machine Learning at 31st International Joint Conference on Artificial Intelligence - 25th European Conference on Artificial Intelligence, IARML@IJCAI-ECAI 2022, Vienna, Austria, 23 July 2022, CEUR Workshop Proceedings Vol. 3174, p. 15-28
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright @ the author(s)
- Rights
- Open Access
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