mlsanityData to 7 Oct 2026

RealKIE: Five Novel Datasets for Enterprise Key Information Extraction

arXiv 2403.20101 ↗First posted 29 Mar 2024cs.CL cs.CV cs.LGcited by 4

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Abstract (arXiv)

We introduce RealKIE, a benchmark of five challenging datasets aimed at advancing key information extraction methods, with an emphasis on enterprise applications. The datasets include a diverse range of documents including SEC S1 Filings, US Non-disclosure Agreements, UK Charity Reports, FCC Invoices, and Resource Contracts. Each presents unique challenges: poor text serialization, sparse annotations in long documents, and complex tabular layouts. These datasets provide a realistic testing ground for key information extraction tasks like investment analysis and contract analysis. In addition to presenting these datasets, we offer an in-depth description of the annotation process, document processing techniques, and baseline modeling approaches. This contribution facilitates the development of NLP models capable of handling practical challenges and supports further research into information extraction technologies applicable to industry-specific problems. The annotated data, OCR outputs, and code to reproduce baselines are available to download at https://indicodatasolutions.github.io/RealKIE/.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 22 of its 45 references that are in the map. First posted on arXiv 29 Mar 2024.

Builds on

22 of 45 references.

References · 22

  1. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  2. 2020Longformer: The Long-Document Transformercited by 3,362
  3. 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,830
  4. 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,219
  5. 2016Hyperband: A Novel Bandit-Based Approach to Hyperparameter Optimizationcited by 688
  6. 2019Quantifying the Carbon Emissions of Machine Learningcited by 516
  7. 2022LayoutLMv3: Pre-training for Document AI with Unified Text and Image Maskingcited by 481
  8. 2019FUNSD: A Dataset for Form Understanding in Noisy Scanned Documentscited by 345
  9. 2021ICDAR2019 Competition on Scanned Receipt OCR and Information Extractioncited by 254
  10. 2021CUAD: An Expert-Annotated NLP Dataset for Legal Contract Reviewcited by 232
  11. 2021ContractNLI: A Dataset for Document-level Natural Language Inference for Contractscited by 145
  12. 2020SciREX: A Challenge Dataset for Document-Level Information Extractioncited by 111
10 more
  1. 2021Kleister: Key Information Extraction Datasets Involving Long Documents with Complex Layoutscited by 82
  2. 2022VRDU: A Benchmark for Visually-rich Document Understandingcited by 35
  3. 2022Efficient Classification of Long Documents Using Transformerscited by 30
  4. 2020A Benchmark for Lease Contract Reviewcited by 26
  5. 2023DocParser: End-to-end OCR-free Information Extraction from Visually Rich Documentscited by 19
  6. 2016Hard Negative Mining for Metric Learning Based Zero-Shot Classificationcited by 18
  7. 2022XDoc: Unified Pre-training for Cross-Format Document Understandingcited by 12
  8. 2021Doc2Dict: Information Extraction as Text Generationcited by 6
  9. 2021Cross-Domain Contract Element Extraction with a Bi-directional Feedback Clause-Element Relation Networkcited by 3
  10. 2022Named Entity Recognition in Industrial Tables using Tabular Language Modelscited by 3

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Citing papers per year: 2026: 4.

4 papers.