Phrase-Indexed Question Answering: A New Challenge for Scalable Document Comprehension
Minjoon Seo, Tom Kwiatkowski, Ankur P. Parikh, Ali Farhadi, Hannaneh Hajishirzi · 2018
We formalize a new modular variant of current question answering tasks by enforcing complete independence of the document encoder from the question encoder.This formulation addresses a key challenge in machine comprehension by requiring a standalone representation of the document discourse.It additionally leads to a significant scalability advantage since the encoding of the answer candidate phrases in the document can be pre-computed and indexed offline for efficient retrieval.We experiment with baseline models for the new task, which achieve a reasonable accuracy but significantly underperform unconstrained QA models.We invite the QA research community to engage in Phrase-Indexed Question Answering (PIQA, pika) for closing the gap.The leaderboard is at: nlp.