# PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution

arXiv: https://arxiv.org/abs/1810.09807 · HTML: https://mlsanity.com/paper/1810.09807/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Oct 2018.

## Built on by (most cited first, 30 of 30)

- [Entity Tracking in Language Models](https://mlsanity.com/paper/2305.02363/) (2023)
- [Modeling Fine-Grained Entity Types with Box Embeddings](https://mlsanity.com/paper/2101.00345/) (2021)
- [On Generalization in Coreference Resolution](https://mlsanity.com/paper/2109.09667/) (2021)
- [Maverick: Efficient and Accurate Coreference Resolution Defying Recent Trends](https://mlsanity.com/paper/2407.21489/) (2024)
- [Moving on from OntoNotes: Coreference Resolution Model Transfer](https://mlsanity.com/paper/2104.08457/) (2021)
- [OntoGUM: Evaluating Contextualized SOTA Coreference Resolution on 12 More Genres](https://mlsanity.com/paper/2106.00933/) (2021)
- [Realistic Evaluation Principles for Cross-document Coreference Resolution](https://mlsanity.com/paper/2106.04192/) (2021)
- [Are Large Language Models Robust Coreference Resolvers?](https://mlsanity.com/paper/2305.14489/) (2023)
- [Schema-learning and rebinding as mechanisms of in-context learning and emergence](https://mlsanity.com/paper/2307.01201/) (2023)
- [Adapting Coreference Resolution Models through Active Learning](https://mlsanity.com/paper/2104.07611/) (2021)
- [Seq2seq is All You Need for Coreference Resolution](https://mlsanity.com/paper/2310.13774/) (2023)
- [Major Entity Identification: A Generalizable Alternative to Coreference Resolution](https://mlsanity.com/paper/2406.14654/) (2024)
- [Who are you referring to? Coreference resolution in image narrations](https://mlsanity.com/paper/2211.14563/) (2022)
- [Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective](https://mlsanity.com/paper/2303.09092/) (2023)
- [Longtonotes: OntoNotes with Longer Coreference Chains](https://mlsanity.com/paper/2210.03650/) (2022)
- [Anatomy of OntoGUM--Adapting GUM to the OntoNotes Scheme to Evaluate Robustness of SOTA Coreference Algorithms](https://mlsanity.com/paper/2110.05727/) (2021)
- [Aggregating Crowdsourced and Automatic Judgments to Scale Up a Corpus of Anaphoric Reference for Fiction and Wikipedia Texts](https://mlsanity.com/paper/2210.05581/) (2022)
- [Multilingual Coreference Resolution in Multiparty Dialogue](https://mlsanity.com/paper/2208.01307/) (2022)
- [ezCoref: Towards Unifying Annotation Guidelines for Coreference Resolution](https://mlsanity.com/paper/2210.07188/) (2022)
- [Advancing Perception in Artificial Intelligence through Principles of Cognitive Science](https://mlsanity.com/paper/2310.08803/) (2023)
- [Solving the Challenge Set without Solving the Task: On Winograd Schemas as a Test of Pronominal Coreference Resolution](https://mlsanity.com/paper/2410.09448/) (2024)
- [Multimodal Coreference Resolution for Chinese Social Media Dialogues: Dataset and Benchmark Approach](https://mlsanity.com/paper/2504.14321/) (2025)
- [QueryBandits for Hallucination Mitigation: Exploiting Semantic Features for No-Regret Rewriting](https://mlsanity.com/paper/2508.16697/) (2025)
- [Review of coreference resolution in English and Persian](https://mlsanity.com/paper/2211.04428/) (2022)
- [Releasing the CRaQAn (Coreference Resolution in Question-Answering): An open-source dataset and dataset creation methodology using instruction-following models](https://mlsanity.com/paper/2311.16338/) (2023)
- [ThaiCoref: Thai Coreference Resolution Dataset](https://mlsanity.com/paper/2406.06000/) (2024)
- [Mah=an=ama: A Unique Testbed for Literary Entity Discovery and Linking](https://mlsanity.com/paper/2509.19844/) (2025)
- [No One Size Fits All: QueryBandits for Hallucination Mitigation](https://mlsanity.com/paper/2602.20332/) (2026)
- [Beyond Word Boundaries: A Hebrew Coreference Benchmark and an Evaluation Protocol for Morphologically Complex Text](https://mlsanity.com/paper/2604.17108/) (2026)
- [Interpretable Coreference Resolution Evaluation Using Explicit Semantics](https://mlsanity.com/paper/2605.10627/) (2026)

## Abstract (arXiv)

We introduce PreCo, a large-scale English dataset for coreference resolution. The dataset is designed to embody the core challenges in coreference, such as entity representation, by alleviating the challenge of low overlap between training and test sets and enabling separated analysis of mention detection and mention clustering. To strengthen the training-test overlap, we collect a large corpus of about 38K documents and 12.4M words which are mostly from the vocabulary of English-speaking preschoolers. Experiments show that with higher training-test overlap, error analysis on PreCo is more efficient than the one on OntoNotes, a popular existing dataset. Furthermore, we annotate singleton mentions making it possible for the first time to quantify the influence that a mention detector makes on coreference resolution performance. The dataset is freely available at https://preschool-lab.github.io/PreCo/.