Abstract
The LAMA (Language Adaptive Method for question Answering) system focuses on answering natural language questions using an RDF knowledge base within a reasonable time. Originally designed to process queries written in French, the system has been redesigned to also function on the English language. Overall, we propose a set of lexico-syntactic patterns for entity and property extraction to create a semantic representation of natural language requests. This semantic representation is then used to generate SPARQL queries able to answer users’ requests. The paper also describes a method for decomposing complex queries into a series of simpler queries. The use of preprocessed data and parallelization methods helps improve individual answer times.
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This research has been partially funded through Canada NSERC Discovery Grant Program.
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Radoev, N., Zouaq, A., Tremblay, M., Gagnon, M. (2018). A Language Adaptive Method for Question Answering on French and English. In: Buscaldi, D., Gangemi, A., Reforgiato Recupero, D. (eds) Semantic Web Challenges. SemWebEval 2018. Communications in Computer and Information Science, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-00072-1_9
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