Representing syntactic-semantic knowledge from English texts
Document Type
Conference Proceeding
Publication Date
1-1-2014
Abstract
We present a unified representational framework LSeN (Language to Semantic Network) for representing syntactic-semantic knowledge extracted from natural language (e.g. English) texts. Our representation is a variant of the standard semantic networks with some important distinctive features that facilitate bridging the interface between syntactic and semantic knowledge using automatic computational tools. We show the basic constructs in our representation and briefly describe the developed tool for automatically building the knowledge structure in LSeN from parsed English sentences. Our representational framework and the associated tool establish a good platform for further studies in automatic knowledge extraction from texts.
Publication Source (Journal or Book title)
Proceedings of the 2014 International Conference on Artificial Intelligence, ICAI 2014 - WORLDCOMP 2014
First Page
237
Last Page
243
Recommended Citation
Guidry, R., & Chen, J. (2014). Representing syntactic-semantic knowledge from English texts. Proceedings of the 2014 International Conference on Artificial Intelligence, ICAI 2014 - WORLDCOMP 2014, 237-243. Retrieved from https://repository.lsu.edu/eecs_pubs/2386