# ANTIQUE: A Non-Factoid Question Answering Benchmark

Source: [ANTIQUE: A Non-Factoid Question Answering Benchmark](<https://www.sota2.com/research/paper/68fa66351e209131cea0ebfd>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T05:58:47.572Z

Authors: Helia Hashemi, Mohammad Aliannejadi, Hamed Zamani, W. Bruce Croft

Published: 2019-05-22T05:32:03.000Z

## Abstract

Considering the widespread use of mobile and voice search, answer passage retrieval for non-factoid questions plays a critical role in modern information retrieval systems. Despite the importance of the task, the community still feels the significant lack of large-scale non-factoid question answering collections with real questions and comprehensive relevance judgments. In this paper, we develop and release a collection of 2,626 open-domain non-factoid questions from a diverse set of categories. The dataset, called ANTIQUE, contains 34,011 manual relevance annotations. The questions were asked by real users in a community question answering service, i.e., Yahoo! Answers. Relevance judgments for all the answers to each question were collected through crowdsourcing. To facilitate further research, we also include a brief analysis of the data as well as baseline results on both classical and recently developed neural IR models.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1905.08957>)

[PDF](<https://arxiv.org/pdf/1905.08957.pdf>)