---
title: "Who cites A Large DataBase of Hypernymy — 22 citing papers"
description: "22 papers of the Elamur Research library cite «A Large DataBase of Hypernymy Relations Extracted from the Web.», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/seitner-2016-large-database-hypernymy-relations-extracted/cited-by/"
---
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# Who cites «A Large DataBase of Hypernymy Relations Extracted from the Web.»

22 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «A Large DataBase of Hypernymy Relations Extracted from the Web.»](https://md.research.elamur.ai/free/en/papers/seitner-2016-large-database-hypernymy-relations-extracted/)

1. **[TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling](https://md.research.elamur.ai/free/en/papers/panchenko-2016-taxi-semeval-2016-task-13/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Alexander Panchenko, Stefano Faralli, Eugen Ruppert, et al.*2016 · 90 citations*
2. **[Every Child Should Have Parents: A Taxonomy Refinement Algorithm Based on Hyperbolic Term Embeddings](https://md.research.elamur.ai/free/en/papers/aly-2019-every-child-should-have-parents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rami Aly, Shantanu Acharya, Alexander Ossa, et al.*2019 · 62 citations*
3. **[Refined Commonsense Knowledge from Large-Scale Web Contents](https://md.research.elamur.ai/free/en/papers/nguyen-2021-refined-commonsense-knowledge-large-scale/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Tuan-Phong Nguyen, Simon Razniewski, Julien Romero, et al.*2021 · 38 citations*

19 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/seitner-2016-large-database-hypernymy-relations-extracted/) — A Large DataBase of Hypernymy Relations Extracted from the Web.