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Answering Complex Open-domain Questions Through Iterative Query Generation

Research article (Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019) · cited 106× · AI/ML
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Answering Complex Open-domain Questions Through Iterative Query Generation

Summary

Answering Complex Open-domain Questions Through Iterative Query Generation is a scholarly article[1].

Key Facts

  • Answering Complex Open-domain Questions Through Iterative Query Generation's instance of is recorded as scholarly article[2].

Related Entities

Christopher D. Manning

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Answering Complex Open-domain Questions Through Iterative Query Generation. Retrieved May 24, 2026, from https://4ort.xyz/entity/answering-complex-open-domain-questions-through-iterative-query-generation
MLA “Answering Complex Open-domain Questions Through Iterative Query Generation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/answering-complex-open-domain-questions-through-iterative-query-generation.
BibTeX @misc{4ortxyz_answering-complex-open-domain-questions-through-iterative-query-generation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Answering Complex Open-domain Questions Through Iterative Query Generation}}, year = {2026}, url = {https://4ort.xyz/entity/answering-complex-open-domain-questions-through-iterative-query-generation}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Answering Complex Open-domain Questions Through Iterative Query Generation — https://4ort.xyz/entity/answering-complex-open-domain-questions-through-iterative-query-generation (retrieved 2026-05-24)

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