Learning the past tense of English verbs using Inductive Logic Programming

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 re sults 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 dened as an ordered list of clauses each ending in a cut Foidl is based on Foil but employs intensional background knowledge and avoids the need for explicit neg ative examples It is particularly useful for problems that involve rules with specic exceptions such as the pasttense task We present results showing that Foidl learns a more accurate pasttense generator from signicantly fewer examples than all previous method