Abstract
This paper presents results on using a new inductive logic programming method called Foidl to learn the past tense of English verbs. The past tense task has been widely studied in the context of the symbolic/connectionist debate. Previous papers have presented results using various neural-network and decision-tree learning methods. We have developed a technique for learning a special type of Prolog program called a first-order decision list, defined as an ordered list of clauses each ending in a cut. Foidl is based on Foil [19] but employs intensional background knowledge and avoids the need for explicit negative examples. It is particularly useful for problems that involve rules with specific exceptions, such as the past-tense task. We present results showing that Foidl learns a more accurate past-tense generator from significantly fewer examples than all previous methods.
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© 1996 Springer-Verlag Berlin Heidelberg
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Mooney, R.J., Califf, M.E. (1996). Learning the past tense of English verbs using inductive logic programming. In: Wermter, S., Riloff, E., Scheler, G. (eds) Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. IJCAI 1995. Lecture Notes in Computer Science, vol 1040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60925-3_60
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DOI: https://doi.org/10.1007/3-540-60925-3_60
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