Process / pipeline
Machine Reading Comprehension (MRC)
Machine reading comprehension (MRC), popularised by the SQuAD benchmark of Rajpurkar, Zhang, Lopyrev and Liang (2016), is a natural-language-processing task in which a model reads a given passage and answers multiple-choice or open-ended questions about it. It turns a passage plus a question into a machine-generated answer, supporting information retrieval, educational technology, and querying research databases.
Open in MethodMindSoonVideoSoon
Read the full method
Members only
Sign inSign in with a free account to read this section.
Sources
- Rajpurkar, P., Zhang, J., Lopyrev, K. & Liang, P. (2016). SQuAD: 100,000+ Questions for Machine Comprehension of Text. EMNLP, 2383-2392. DOI: 10.18653/v1/D16-1264 ↗
- Yang, Z. et al. (2018). HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. EMNLP. DOI: 10.18653/v1/D18-1259 ↗