mlsanityData to 7 Oct 2026

TweetNERD -- End to End Entity Linking Benchmark for Tweets

arXiv 2210.08129 ↗First posted 14 Oct 2022cs.CL cs.AI cs.IRcited by 4

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Abstract (arXiv)

Named Entity Recognition and Disambiguation (NERD) systems are foundational for information retrieval, question answering, event detection, and other natural language processing (NLP) applications. We introduce TweetNERD, a dataset of 340K+ Tweets across 2010-2021, for benchmarking NERD systems on Tweets. This is the largest and most temporally diverse open sourced dataset benchmark for NERD on Tweets and can be used to facilitate research in this area. We describe evaluation setup with TweetNERD for three NERD tasks: Named Entity Recognition (NER), Entity Linking with True Spans (EL), and End to End Entity Linking (End2End); and provide performance of existing publicly available methods on specific TweetNERD splits. TweetNERD is available at: https://doi.org/10.5281/zenodo.6617192 under Creative Commons Attribution 4.0 International (CC BY 4.0) license. Check out more details at https://github.com/twitter-research/TweetNERD.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 10 of its 51 references that are in the map. First posted on arXiv 14 Oct 2022.

Builds on

10 of 51 references.

References · 10

  1. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  2. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
  3. 2020BERTweet: A pre-trained language model for English Tweetscited by 346
  4. 2020Autoregressive Entity Retrievalcited by 333
  5. 2017Semi-supervised sequence tagging with bidirectional language modelscited by 86
  6. 2020REL: An Entity Linker Standing on the Shoulders of Giantscited by 61
  7. 2020Assessing Demographic Bias in Named Entity Recognitioncited by 23
  8. 2014Analysis of Named Entity Recognition and Linking for Tweetscited by 20
  9. 2016S-MART: Novel Tree-based Structured Learning Algorithms Applied to Tweet Entity Linkingcited by 16
  10. 2021LMSOC: An Approach for Socially Sensitive Pretrainingcited by 8

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 0; 2026: 1.

4 papers.

  1. 2023SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Researchcited by 9
  2. 2023Multi-Modal Discussion Transformer: Integrating Text, Images and Graph Transformers to Detect Hate Speech on Social Mediacited by 6
  3. 2024A Systematic Analysis on the Temporal Generalization of Language Models in Social Mediacited by 0
  4. 2026Scalable Model-Based Clustering with Sequential Monte Carlocited by 0