acl acl2011 acl2011-237 acl2011-237-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Jenny Liu ; Aria Haghighi
Abstract: In this work, we present a novel approach to the generation task of ordering prenominal modifiers. We take a maximum entropy reranking approach to the problem which admits arbitrary features on a permutation of modifiers, exploiting hundreds ofthousands of features in total. We compare our error rates to the state-of-the-art and to a strong Google ngram count baseline. We attain a maximum error reduction of 69.8% and average error reduction across all test sets of 59. 1% compared to the state-of-the-art and a maximum error reduction of 68.4% and average error reduction across all test sets of 41.8% compared to our Google n-gram count baseline.