Active Tags for Semantic Analysis
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Discriminative Training of the Hidden Vector State Model for Semantic Parsing
IEEE Transactions on Knowledge and Data Engineering
Hybrid semantic analysis system - ATIS data evaluation
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
SWSNL: Semantic Web Search Using Natural Language
Expert Systems with Applications: An International Journal
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In this paper, a methodology of semantic annotation of the LingvoSemantic corpus is presented. Semantic annotation is usually a time consuming and expensive process. We thus developed a methodology that significantly reduces the demands of the process. The methodology consists of a set of techniques and computer tools designed to simplify the process as much as possible. We claim that in this way it is possible to obtain sufficient amount of annotated data in a reasonable time frame. The LingvoSemantic project focuses on semantic analysis of user questions to an Internet information retrieval system. The semantic representation approach is based on abstract semantic annotation methodology. However, we advanced the annotation process. The bootstrapping method was used during the corpus annotation. The resulting annotated corpus consists of 20292 annotated sentences. In comparison to the straight-forward style of annotation, our approach significantly improved the efficiency of the annotation. The results, as well as a set of recommendations for creating the annotated data, are presented at the end of the paper.