Paper: Linguistic Knowledge Generator

ACL ID C92-2085
Title Linguistic Knowledge Generator
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1992

(;'r,, : Gredit of instance tuple 7' with identification mmfl, er i, {0, 1] V,,~ : Plausibility value of a hypothesis-tuple T in cycle 9. [0, 1] D~ (w. ,rvb) : distance between words, w~ and wb m cycle 9. TO, 11 Algorithm The following explanation of the algorithm assumes that the illlnlts are sentences. 1 For a sentence we use a simple grammar to find all tuples lmssibly used. Each instance-tuple is then given credit in proportion to the number of conlpeting tuples. 1 (~ = (1) number of competing tuples This credit sbows which rules are suitable for this sentence. On the first iteration the split of the credit between ambiguous analyses is uniform as shown above, but on subsequent iterations plausibility values of tire hypothesis-tuples VT a-1 before the iteration are used to give prefere...