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Computational models can be built to capture the syntactic structures and semantic patterns of human punning riddles. This model is then used as rules by a computer to generate its own puns. This paper presents T-PEG, a system that utilizes phonetic and semantic linguistic resources to automatically extract word relationships in puns and store the knowledge(More)
The design and content of the planning library of a story generation system dictates the content quality of the story it produces. This paper presents the story planner component of Picture Books, a system that generates stories for children aged 4 to 6 years based on a set of picture elements selected by the user. The planning library separates the design(More)
Humor is an integral part of our day-to-day communication making it interesting and plausible. The growing demand in robotics and the constant urge for machines to pass the Turing test to eliminate the thin line difference between human and machine behavior make it essential for machines to be able to use humor in communication. Moreover, Learning is a(More)
Text generation systems, such as pun generators, depend on manually created templates which require a lot of effort to build. This paper presents T-Peg, a system that utilizes semantic and phonetic knowledge sources to automatically capture the wordplay patterns of human-made jokes from training examples. The knowledge learned are stored as templates which,(More)
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(More)
  • Ethel Ong, Kathleen Go, Vince Andrew Nuñez, Manimin Morga, Francis Veto
  • 2007
This paper presents a template-based machine translation system that extracts templates from a given bilingual corpus, then uses these templates to perform bi-directional EnglishFilipino translations. The system extended the similarity template learning algorithm of Cicekli and Guvenir [2] by refining existing templates and deriving templates from(More)