Categorizing Comparative Sentences
Alexander Panchenko, Alexander Bondarenko, Mirco Franzek, Matthias Hagen, Chris Biemann · 2019
We tackle the tasks of automatically identifying comparative sentences and categorizing the intended preference (e.g., "Python has better NLP libraries than MATLAB" → Python, better, MATLAB).To this end, we manually annotate 7,199 sentences for 217 distinct target item pairs from several domains (27% of the sentences contain an oriented comparison in the sense of "better" or "worse").A gradient boosting model based on pre-trained sentence embeddings reaches an F1 score of 85% in our experimental evaluation.The model can be used to extract comparative sentences for pro/con argumentation in comparative / argument search engines or debating technologies.