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

COLING 2016  ·  Harish Tayyar Madabushi, Mark 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{\%}... Additionally, we believe that machine learning algorithms can be applied on top of this method to further improve accuracy. read more

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Results from the Paper

Task Dataset Model Metric Name Metric Value Global Rank Benchmark
Text Classification TREC-50 Rules Error 2.8 # 1


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