High Accuracy Rule-based Question Classification using Question Syntax and Semantics

COLING 2016 Harish Tayyar MadabushiMark Lee

We present in this paper a purely rule-based system for Question Classification which we divide into two parts: The first is the extraction of relevant words from a question by use of its structure, and the second is the classification of questions based on rules that associate these words to Concepts. We achieve an accuracy of 97.2{\%}, close to a 6 point improvement over the previous State of the Art of 91.6{\%}... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Text Classification TREC-50 Rules Error 2.8 # 1