mlsanityData to 7 Oct 2026

Asking It All: Generating Contextualized Questions for any Semantic Role

arXiv 2109.04832 ↗First posted 10 Sep 2021cs.CLcited by 22

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Abstract (arXiv)

Asking questions about a situation is an inherent step towards understanding it. To this end, we introduce the task of role question generation, which, given a predicate mention and a passage, requires producing a set of questions asking about all possible semantic roles of the predicate. We develop a two-stage model for this task, which first produces a context-independent question prototype for each role and then revises it to be contextually appropriate for the passage. Unlike most existing approaches to question generation, our approach does not require conditioning on existing answers in the text. Instead, we condition on the type of information to inquire about, regardless of whether the answer appears explicitly in the text, could be inferred from it, or should be sought elsewhere. Our evaluation demonstrates that we generate diverse and well-formed questions for a large, broad-coverage ontology of predicates and roles.

Key facts. Cited by 22 papers in the map (data through 7 Oct 2026). Builds on 17 of its 33 references that are in the map. First posted on arXiv 10 Sep 2021.

Builds on

17 of 33 references.

References · 17

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  3. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  4. 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,538
  5. 2017Zero-Shot Relation Extraction via Reading Comprehensioncited by 425
  6. 2018AllenNLP: A Deep Semantic Natural Language Processing Platformcited by 347
  7. 2017Learning to Ask: Neural Question Generation for Reading Comprehensioncited by 186
  8. 2020Event Extraction by Answering (Almost) Natural Questionscited by 177
  9. 2019Simple BERT Models for Relation Extraction and Semantic Role Labelingcited by 154
  10. 2019Asking Clarifying Questions in Open-Domain Information-Seeking Conversationscited by 136
  11. 2019Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generationcited by 75
  12. 2018Large-Scale QA-SRL Parsingcited by 45
5 more
  1. 2019Controlled Crowdsourcing for High-Quality QA-SRL Annotationcited by 34
  2. 2020QADiscourse -- Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselinescited by 34
  3. 2020Stay Hungry, Stay Focused: Generating Informative and Specific Questions in Information-Seeking Conversationscited by 19
  4. 2018Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Typescited by 17
  5. 2020Syn-QG: Syntactic and Shallow Semantic Rules for Question Generationcited by 12

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Citing papers per year: 2022: 10; 2023: 7; 2024: 4; 2025: 1.

22 papers.

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  1. 2022Generating Literal and Implied Subquestions to Fact-check Complex Claimscited by 66
  2. 2022Conditional Generation with a Question-Answering Blueprintcited by 44
  3. 2022Generative Language Models for Paragraph-Level Question Generationcited by 28
  4. 2023Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answeringcited by 28
  5. 2022Educational Question Generation of Children Storybooks via Question Type Distribution Learning and Event-Centric Summarizationcited by 26
  6. 2022Selecting Better Samples from Pre-trained LLMs: A Case Study on Question Generationcited by 17
  7. 2023An Empirical Comparison of LM-based Question and Answer Generation Methodscited by 15
  8. 2023A Practical Toolkit for Multilingual Question and Answer Generationcited by 10
  9. 2025NLI under the Microscope: What Atomic Hypothesis Decomposition Revealscited by 9
  10. 2022"What makes a question inquisitive?" A Study on Type-Controlled Inquisitive Question Generationcited by 7
  11. 2022Semantic Role Labeling Meets Definition Modeling: Using Natural Language to Describe Predicate-Argument Structurescited by 4
  12. 2024Promptly Predicting Structures: The Return of Inferencecited by 4
10 more
  1. 2024Explicating the Implicit: Argument Detection Beyond Sentence Boundariescited by 4
  2. 2023DIFFQG: Generating Questions to Summarize Factual Changescited by 3
  3. 2024Graph Guided Question Answer Generation for Procedural Question-Answeringcited by 3
  4. 2022Ask to Understand: Question Generation for Multi-hop Question Answeringcited by 2
  5. 2022Repro: An Open-Source Library for Improving the Reproducibility and Usability of Publicly Available Research Codecited by 2
  6. 2023Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessmentcited by 2
  7. 2023The Case for Scalable, Data-Driven Theory: A Paradigm for Scientific Progress in NLPcited by 2
  8. 2022Dense Paraphrasing for Textual Enrichmentcited by 1
  9. 2024QOG:Question and Options Generation based on Language Modelcited by 1
  10. 2023Modeling Complex Event Scenarios via Simple Entity-focused Questionscited by 0