Modeling Biological Processes for Reading Comprehension - Jonathan Berant

Abstract:
Machine reading calls for programs that read and understand text, but most current work only attempts to extract facts from redundant web-scale corpora. In this talk, I will focus on a new reading comprehension task that requires complex reasoning over a single document. The input is a paragraph describing a biological process, and the goal is to answer questions that require an understanding of the relations between entities and events in the
process. To answer the questions, we first predict a rich structure representing the
process in the paragraph. Then, we map the question to a formal query, which is executed against the predicted structure. We demonstrate that answering questions via predicted structures substantially improves accuracy over baselines that use shallower representations.

[katirasoleymanzadeh]

Dear Jonathan, I have a question about the annotation process. Have you asked annotators to write just one question for each paragraph or multiple questions for each?