---
title: "Who cites Question-Answer Driven Semantic Role Labeling…"
description: "The papers of the Elamur Research library that cite «Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language»…"
canonical: "https://research.elamur.ai/free/en/papers/he-2015-question-answer-driven-semantic-role/cited-by/"
---
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# Who cites «Question-Answer Driven Semantic Role Labeling: Using Natural Language to Annotate Natural Language»

127 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/he-2015-question-answer-driven-semantic-role/)

Pages: **1** · [2](https://md.research.elamur.ai/free/en/papers/he-2015-question-answer-driven-semantic-role/cited-by/page/2/)

1. [Effective QA-Driven Annotation of Predicate–Argument Relations Across Languages](https://aclanthology.org/2026.eacl-long.112/) *— 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
2. [Learning from Child-directed Speech in Two-language Scenarios: A French-English Case-Study](https://aclanthology.org/2026.findings-eacl.337/) *— 2026 · Findings of the Association for Computational Linguistics: EACL 2026*
3. [A Survey of QUD Models for Discourse Processing](https://md.research.elamur.ai/free/en/papers/fu-2025-survey-qud-models-discourse-processing/) *— our card · 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
4. [A Systematic Survey of Semantic Role Labeling in the Era of Pretrained Language Models](https://arxiv.org/abs/2502.08660) *— 2025 · arXiv:2502.08660*
5. [ASQ: Automatically Generating Question-Answer Pairs Using AMRs](https://aclanthology.org/2025.ranlp-1.115/) *— 2025 · Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era*
6. [Are LLMs Good for Semantic Role Labeling via Question Answering?: A Preliminary Analysis](https://aclanthology.org/2025.ijcnlp-srw.21/) *— 2025 · The 14th International Joint Conference on Natural Language Processing and The 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
7. [Beyond Output Matching: Bidirectional Alignment for Enhanced In-Context Learning](https://aclanthology.org/2025.acl-long.1573/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
8. [Injecting Frame Semantics into Large Language Models via Prompt-Based Fine-Tuning](https://aclanthology.org/2025.starsem-1.3/) *— 2025 · Proceedings of the 14th Joint Conference on Lexical and Computational Semantics (*SEM 2025)*
9. [Prototype Conditioned Generative Replay for Continual Learning in NLP](https://aclanthology.org/2025.naacl-long.636/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
10. [QA-Noun: Representing Nominal Semantics via Natural Language Question-Answer Pairs](https://aclanthology.org/2025.ijcnlp-long.147/) *— 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
11. [A Survey on Open Information Extraction from Rule-based Model to Large Language Model](https://aclanthology.org/2024.findings-emnlp.560/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
12. [Asking and Answering Questions to Extract Event-Argument Structures](https://aclanthology.org/2024.lrec-main.142/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
13. [BenchIE\textasciicircumFL: A Manually Re-Annotated Fact-Based Open Information Extraction Benchmark](https://aclanthology.org/2024.findings-acl.496/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
14. [Explicating the Implicit: Argument Detection Beyond Sentence Boundaries](https://aclanthology.org/2024.acl-long.863/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
15. [Investigating the Generalizability of Pretrained Language Models across Multiple Dimensions: A Case Study of NLI and MRC](https://aclanthology.org/2024.genbench-1.11/) *— 2024 · Proceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLP*
16. [OMoS-QA: A Dataset for Cross-Lingual Extractive Question Answering in a German Migration Context](https://aclanthology.org/2024.konvens-main.25/) *— 2024 · Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024)*
17. [Promptly Predicting Structures: The Return of Inference](https://aclanthology.org/2024.naacl-long.7/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
18. [QA-based Event Start-Points Ordering for Clinical Temporal Relation Annotation](https://aclanthology.org/2024.lrec-main.1171/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
19. [QAEVENT: Event Extraction as Question-Answer Pairs Generation](https://aclanthology.org/2024.findings-eacl.126/) *— 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
20. [SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graph](https://aclanthology.org/2024.acl-long.238/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
21. [Semantic Role Labeling from Chinese Speech via End-to-End Learning](https://aclanthology.org/2024.findings-acl.527/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
22. [TransAlign: An Automated Corpus Generation through Cross-Linguistic Data Alignment for Open Information Extraction](https://aclanthology.org/2024.propor-1.20/) *— 2024 · Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1*
23. [Bootstrapping Small & High Performance Language Models with Unmasking-Removal Training Policy](https://aclanthology.org/2023.emnlp-main.30/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
24. [Conditional Generation with a Question-Answering Blueprint](https://aclanthology.org/2023.tacl-1.55/) *— 2023 · Transactions of the Association for Computational Linguistics*
25. [Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion](https://md.research.elamur.ai/free/en/papers/ko-2023-discourse-analysis-questions-answers-parsing/) *— our card · 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
26. [Domain Incremental Lifelong Learning in an Open World](https://aclanthology.org/2023.findings-acl.361/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
27. [Few-shot Adaptation Works with UnpredicTable Data](https://aclanthology.org/2023.acl-long.102/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
28. [Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?](https://aclanthology.org/2023.acl-long.659/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
29. [Lifelong Sequence Generation with Dynamic Module Expansion and Adaptation](https://aclanthology.org/2023.emnlp-main.414/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
30. [My side, your side and the evidence: Discovering aligned actor groups and the narratives they weave](https://aclanthology.org/2023.acl-long.497/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
31. [Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering](https://aclanthology.org/2023.acl-long.110/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
32. [Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction](https://aclanthology.org/2023.emnlp-main.360/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
33. [PropSegmEnt: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment Recognition](https://aclanthology.org/2023.findings-acl.565/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
34. [QA-Adj: Adding Adjectives to QA-based Semantics](https://aclanthology.org/2023.dmr-1.8/) *— 2023 · Proceedings of the Fourth International Workshop on Designing Meaning Representations*
35. [QA-NatVer: Question Answering for Natural Logic-based Fact Verification](https://aclanthology.org/2023.emnlp-main.521/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
36. [The Case for Scalable, Data-Driven Theory: A Paradigm for Scientific Progress in NLP](https://aclanthology.org/2023.bigpicture-1.4/) *— 2023 · Proceedings of the Big Picture Workshop*
37. [Verifying Annotation Agreement without Multiple Experts: A Case Study with Gujarati SNACS](https://aclanthology.org/2023.findings-acl.696/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
38. [WiCE: Real-World Entailment for Claims in Wikipedia](https://aclanthology.org/2023.emnlp-main.470/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
39. [ZEROTOP: Zero-Shot Task-Oriented Semantic Parsing using Large Language Models](https://aclanthology.org/2023.emnlp-main.354/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
40. [A Question-Answer Driven Approach to Reveal Affirmative Interpretations from Verbal Negations](https://aclanthology.org/2022.findings-naacl.37/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
41. [A Semantics-Aware Approach to Automated Claim Verification](https://aclanthology.org/2022.fever-1.5/) *— 2022 · Proceedings of the Fifth Fact Extraction and VERification Workshop (FEVER)*
42. [An MRC Framework for Semantic Role Labeling](https://aclanthology.org/2022.coling-1.191/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
43. [BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation](https://aclanthology.org/2022.acl-long.307/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
44. [CANarEx: Contextually Aware Narrative Extraction for Semantically Rich Text-as-data Applications](https://aclanthology.org/2022.findings-emnlp.260/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
45. [Competence-based Question Generation](https://aclanthology.org/2022.coling-1.131/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
46. [DeepStruct: Pretraining of Language Models for Structure Prediction](https://aclanthology.org/2022.findings-acl.67/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
47. [Different Tunes Played with Equal Skill: Exploring a Unified Optimization Subspace for Parameter-Efficient Tuning](https://aclanthology.org/2022.findings-emnlp.244/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
48. [Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?](https://aclanthology.org/2022.findings-emnlp.206/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
49. [Eliciting and Understanding Cross-task Skills with Task-level Mixture-of-Experts](https://aclanthology.org/2022.findings-emnlp.189/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
50. [Generating Literal and Implied Subquestions to Fact-check Complex Claims](https://aclanthology.org/2022.emnlp-main.229/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
51. [Heroes, Villains, and Victims, and GPT-3: Automated Extraction of Character Roles Without Training Data](https://aclanthology.org/2022.wnu-1.6/) *— 2022 · Proceedings of the 4th Workshop of Narrative Understanding (WNU2022)*
52. [LMTurk: Few-Shot Learners as Crowdsourcing Workers in a Language-Model-as-a-Service Framework](https://aclanthology.org/2022.findings-naacl.51/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
53. [QASem Parsing: Text-to-text Modeling of QA-based Semantics](https://aclanthology.org/2022.emnlp-main.528/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
54. [Question Answering Infused Pre-training of General-Purpose Contextualized Representations](https://aclanthology.org/2022.findings-acl.59/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
55. [SRL4E – Semantic Role Labeling for Emotions: A Unified Evaluation Framework](https://aclanthology.org/2022.acl-long.314/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
56. [SemEval-2022 Task 9: R2VQ – Competence-based Multimodal Question Answering](https://aclanthology.org/2022.semeval-1.176/) *— 2022 · Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)*
57. [Semantic Role Labeling Meets Definition Modeling: Using Natural Language to Describe Predicate-Argument Structures](https://aclanthology.org/2022.findings-emnlp.313/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
58. [Text-based NP Enrichment](https://aclanthology.org/2022.tacl-1.44/) *— 2022 · Transactions of the Association for Computational Linguistics*
59. [Universal Semantic Annotator: the First Unified API for WSD, SRL and Semantic Parsing](https://aclanthology.org/2022.lrec-1.282/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
60. [Asking It All: Generating Contextualized Questions for any Semantic Role](https://aclanthology.org/2021.emnlp-main.108/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
61. [Can predicate-argument relationships be extracted from UD trees?](https://md.research.elamur.ai/free/en/papers/ek-2021-can-predicate-argument-relationships-be/) *— our card · 2021 · Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop*
62. [Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence](https://aclanthology.org/2021.findings-acl.371/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
63. [CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP](https://arxiv.org/abs/2104.08835) *— 2021 · arXiv:2104.08835*
64. [DocOIE: A Document-level Context-Aware Dataset for OpenIE](https://aclanthology.org/2021.findings-acl.210/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
65. [Event-Centric Natural Language Processing](https://aclanthology.org/2021.acl-tutorials.2/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Tutorial Abstracts*
66. [Finetuned Language Models Are Zero-Shot Learners](https://arxiv.org/abs/2109.01652) *— 2021 · arXiv:2109.01652*
67. [InVeRo-XL: Making Cross-Lingual Semantic Role Labeling Accessible with Intelligible Verbs and Roles](https://aclanthology.org/2021.emnlp-demo.36/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
68. [Inducing Semantic Roles Without Syntax](https://aclanthology.org/2021.findings-acl.389/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
69. [LSOIE: A Large-Scale Dataset for Supervised Open Information Extraction](https://aclanthology.org/2021.eacl-main.222/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
70. [Learning Syntax from Naturally-Occurring Bracketings](https://aclanthology.org/2021.naacl-main.234/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
71. [MetaICL: Learning to Learn In Context](https://arxiv.org/abs/2110.15943) *— 2021 · arXiv:2110.15943*
72. [QA-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer Propositions](https://aclanthology.org/2021.emnlp-main.778/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
73. [QA-Driven Zero-shot Slot Filling with Weak Supervision Pretraining](https://aclanthology.org/2021.acl-short.83/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
74. [ReadOnce Transformers: Reusable Representations of Text for Transformers](https://aclanthology.org/2021.acl-long.554/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
75. [SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/) *— our card · 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
76. [Self Question-answering: Aspect-based Sentiment Analysis by Role Flipped Machine Reading Comprehension](https://aclanthology.org/2021.findings-emnlp.115/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
77. [Self-Supervised Test-Time Learning for Reading Comprehension](https://aclanthology.org/2021.naacl-main.95/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
78. [UniteD-SRL: A Unified Dataset for Span- and Dependency-Based Multilingual and Cross-Lingual Semantic Role Labeling](https://aclanthology.org/2021.findings-emnlp.197/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
79. [WeaQA: Weak Supervision via Captions for Visual Question Answering](https://aclanthology.org/2021.findings-acl.302/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
80. [Zero-Shot Information Extraction as a Unified Text-to-Triple Translation](https://aclanthology.org/2021.emnlp-main.94/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
81. [A Novel Workflow for Accurately and Efficiently Crowdsourcing Predicate Senses and Argument Labels](https://aclanthology.org/2020.findings-emnlp.38/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
82. [Asking without Telling: Exploring Latent Ontologies in Contextual Representations](https://aclanthology.org/2020.emnlp-main.552/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
83. [Automated Graph Generation at Sentence Level for Reading Comprehension Based on Conceptual Graphs](https://aclanthology.org/2020.coling-main.240/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
84. [Bridging the Gap in Multilingual Semantic Role Labeling: a Language-Agnostic Approach](https://aclanthology.org/2020.coling-main.120/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
85. [Controlled Crowdsourcing for High-Quality QA-SRL Annotation](https://md.research.elamur.ai/free/en/papers/roit-2020-controlled-crowdsourcing-high-quality-qa/) *— our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
86. [CorefQA: Coreference Resolution as Query-based Span Prediction](https://aclanthology.org/2020.acl-main.622/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
87. [Distill and Replay for Continual Language Learning](https://aclanthology.org/2020.coling-main.318/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
88. [InVeRo: Making Semantic Role Labeling Accessible with Intelligible Verbs and Roles](https://aclanthology.org/2020.emnlp-demos.11/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
89. [Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?](https://aclanthology.org/2020.acl-main.467/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
90. [Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases](https://arxiv.org/abs/2009.11564) *— 2020 · arXiv:2009.11564 (Foundations and Trends in Databases, 2021)*
91. [QADiscourse - Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines](https://aclanthology.org/2020.emnlp-main.224/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
92. [QANom: Question-Answer driven SRL for Nominalizations](https://md.research.elamur.ai/free/en/papers/klein-2020-qanom-question-answer-driven-srl/) *— our card · 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
93. [QuASE: Question-Answer Driven Sentence Encoding](https://aclanthology.org/2020.acl-main.772/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
94. [Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback](https://aclanthology.org/2020.acl-main.187/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
95. [Syntactic and Semantic-driven Learning for Open Information Extraction](https://aclanthology.org/2020.findings-emnlp.69/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
96. [TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions](https://md.research.elamur.ai/free/en/papers/ning-2020-torque-reading-comprehension-dataset-temporal/) *— our card · 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
97. [“Who said it, and Why?” Provenance for Natural Language Claims](https://aclanthology.org/2020.acl-main.406/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
98. [pyBART: Evidence-based Syntactic Transformations for IE](https://md.research.elamur.ai/free/en/papers/ud-2020-tiktinsky-pybart-evidence-based-syntactic-transformations/) *— our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations*
99. [CaRB: A Crowdsourced Benchmark for Open IE](https://aclanthology.org/D19-1651/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
100. [Combining Knowledge Hunting and Neural Language Models to Solve the Winograd Schema Challenge](https://aclanthology.org/P19-1614/) *— 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics*

Pages: **1** · [2](https://md.research.elamur.ai/free/en/papers/he-2015-question-answer-driven-semantic-role/cited-by/page/2/)