# Reddit Entity Linking Dataset

arXiv: https://arxiv.org/abs/2101.01228 · HTML: https://mlsanity.com/paper/2101.01228/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 29 of its 58 references that are in the map.
- First posted on arXiv 4 Jan 2021.

## Builds on (most cited first, 29 of 29)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention](https://mlsanity.com/paper/2010.01057/) (2020)
- [A Knowledge-Grounded Neural Conversation Model](https://mlsanity.com/paper/1702.01932/) (2017)
- [Zero-Shot Entity Linking by Reading Entity Descriptions](https://mlsanity.com/paper/1906.07348/) (2019)
- [A Survey on Recent Advances in Named Entity Recognition from Deep Learning models](https://mlsanity.com/paper/1910.11470/) (2019)
- [End-to-End Neural Entity Linking](https://mlsanity.com/paper/1808.07699/) (2018)
- [Dreaddit: A Reddit Dataset for Stress Analysis in Social Media](https://mlsanity.com/paper/1911.00133/) (2019)
- [Deep Joint Entity Disambiguation with Local Neural Attention](https://mlsanity.com/paper/1704.04920/) (2017)
- [Linguistically-Informed Self-Attention for Semantic Role Labeling](https://mlsanity.com/paper/1804.08199/) (2018)
- [A Large Self-Annotated Corpus for Sarcasm](https://mlsanity.com/paper/1704.05579/) (2017)
- [Open-World Knowledge Graph Completion](https://mlsanity.com/paper/1711.03438/) (2017)
- [REL: An Entity Linker Standing on the Shoulders of Giants](https://mlsanity.com/paper/2006.01969/) (2020)
- [Improving Entity Linking by Modeling Latent Relations between Mentions](https://mlsanity.com/paper/1804.10637/) (2018)
- [Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking](https://mlsanity.com/paper/2003.05473/) (2020)
- [Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation](https://mlsanity.com/paper/1601.01343/) (2016)
- [Neural Entity Linking: A Survey of Models Based on Deep Learning](https://mlsanity.com/paper/2006.00575/) (2020)
- [DeepType: Multilingual Entity Linking by Neural Type System Evolution](https://mlsanity.com/paper/1802.01021/) (2018)
- [GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension](https://mlsanity.com/paper/1908.00059/) (2019)
- [Fine-Grained Entity Typing for Domain Independent Entity Linking](https://mlsanity.com/paper/1909.05780/) (2019)
- [Context-Dependent Fine-Grained Entity Type Tagging](https://mlsanity.com/paper/1412.1820/) (2014)
- [Joint Entity Linking with Deep Reinforcement Learning](https://mlsanity.com/paper/1902.00330/) (2019)
- [Analysis of Named Entity Recognition and Linking for Tweets](https://mlsanity.com/paper/1410.7182/) (2014)
- [Learning Dynamic Context Augmentation for Global Entity Linking](https://mlsanity.com/paper/1909.02117/) (2019)
- [Neural Architectures for Fine-grained Entity Type Classification](https://mlsanity.com/paper/1606.01341/) (2016)
- [Boosting Entity Linking Performance by Leveraging Unlabeled Documents](https://mlsanity.com/paper/1906.01250/) (2019)
- [Changing Views: Persuasion Modeling and Argument Extraction from Online Discussions](https://mlsanity.com/paper/1907.06076/) (2019)
- [Twitter for Sparking a Movement, Reddit for Sharing the Moment: #metoo through the Lens of Social Media](https://mlsanity.com/paper/1803.08022/) (2018)
- [She's Reddit: A source of statistically significant gendered interest information?](https://mlsanity.com/paper/1810.08091/) (2018)

## Built on by (most cited first, 7 of 7)

- [ChatEL: Entity Linking with Chatbots](https://mlsanity.com/paper/2402.14858/) (2024)
- [Entity Disambiguation via Fusion Entity Decoding](https://mlsanity.com/paper/2404.01626/) (2024)
- [DynamicER: Resolving Emerging Mentions to Dynamic Entities for RAG](https://mlsanity.com/paper/2410.11494/) (2024)
- [Posthoc Verification and the Fallibility of the Ground Truth](https://mlsanity.com/paper/2106.07353/) (2021)
- [Building an Icelandic Entity Linking Corpus](https://mlsanity.com/paper/2206.05014/) (2022)
- [Cross-Domain Neural Entity Linking](https://mlsanity.com/paper/2210.15616/) (2022)
- [Select, Don't Train: The Benefits of Modular Entity Disambiguation with LLM-Based Selection](https://mlsanity.com/paper/2608.27470/) (2026)

## Abstract (arXiv)

We introduce and make publicly available an entity linking dataset from Reddit that contains 17,316 linked entities, each annotated by three human annotators and then grouped into Gold, Silver, and Bronze to indicate inter-annotator agreement. We analyze the different errors and disagreements made by annotators and suggest three types of corrections to the raw data. Finally, we tested existing entity linking models that are trained and tuned on text from non-social media datasets. We find that, although these existing entity linking models perform very well on their original datasets, they perform poorly on this social media dataset. We also show that the majority of these errors can be attributed to poor performance on the mention detection subtask. These results indicate the need for better entity linking models that can be applied to the enormous amount of social media text.