Interpreting Answers to Yes-No Questions in User-Generated Content

Shivam Mathur, Keun Hee Park, Dhivya Chinnappa, Saketh Kotamraju, Eduardo Blanco

Submission Type: Regular Long Paper

Submission Track: Question Answering

Submission Track 2: NLP Applications

Keywords: yes-no questions, question answering

TL;DR: Understanding what answers to yes-no type questions mean in user-generated content

Abstract: Interpreting answers to yes-no questions in social media is difficult. Yes and no keywords are uncommon, and the few answers that include them are rarely to be interpreted what the keywords suggest. In this paper, we present a new corpus of 4,442 yes-no question-answer pairs from Twitter. We discuss linguistic characteristics of answers whose interpretation is yes or no, as well as answers whose interpretation is unknown. We show that large language models are far from solving this problem, even after fine-tuning and blending other corpora for the same problem but outside social media.

Submission Number: 1137