Automatically extracting templates from examples for NLP tasks
College of Computer Studies
Proceedings of the 22nd Pacific Asia Conference on Language, Information and Computation, PACLIC 22
In this paper, we present the approaches used by our NLP systems to automatically extract templates for example-based machine translation and pun generation. Our translation system is able to extract an average of 73.25% correct translation templates, resulting in a translation quality that has a low word error rate of 18% when the test document contains sentence patterns matching the training set, to a high 85% when the test document is different from the training corpus. Our pun generator is able to extract 69.2% usable templates, resulting in computer-generated puns that received an average score of 2.13 as compared to 2.7 for human-generated puns from user feedback. © 2007 by Ethel Ong, Bryan Anthony Hong, and Vince Andrew Nuñez.
Ong, E., Hong, B., & Nuñez, V. (2008). Automatically extracting templates from examples for NLP tasks. Proceedings of the 22nd Pacific Asia Conference on Language, Information and Computation, PACLIC 22, 452-459. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/500
Machine translating; Natural language generation (Computer science); Wit and humor