Title :
High precision logic form transformation
Author_Institution :
Dept. of Comput. Sci. & Eng., Southern Methodist Univ., Dallas, TX, USA
Abstract :
This paper presents few extensions to the logic form representation and a method for transforming WordNet glosses into logic forms using a set of high-precision rules combined with a set of high recall heuristics. An almost 3% increase in POS tagging accuracy is achieved over state-of-the art results at the expense of user intervention on only 7.52% of words. We apply a nearest neighbor solution to parser switching that leads to 6.43% increase in exact sentence accuracy for glosses. Logic Forms are derived with an accuracy of 89.46%
Keywords :
grammars; information retrieval; natural languages; POS tagging accuracy; WordNet glosses; high precision logic form transformation; nearest neighbor solution; parser switching; recall heuristics; user intervention; Art; Automatic logic units; Computer science; Data mining; Dictionaries; Lenses; Nearest neighbor searches; Tagging; Taxonomy; Voting;
Conference_Titel :
Tools with Artificial Intelligence, Proceedings of the 13th International Conference on
Conference_Location :
Dallas, TX
Print_ISBN :
0-7695-1417-0
DOI :
10.1109/ICTAI.2001.974476