RealKIE-FCC
Progress Over Time
Interactive timeline showing model performance evolution on RealKIE-FCC
RealKIE-FCC Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Amazon | — | — | — | ||
| 2 | Amazon | — | 1.0M | $0.30 / $2.50 | ||
| 3 | Amazon | — | — | — |
What is RealKIE-FCC?
RealKIE-FCC is a key information extraction benchmark drawn from real enterprise documents (FCC filings), part of the RealKIE suite of five novel datasets for enterprise key information extraction. Models must convert documents to markdown and extract structured fields against a specified JSON schema. Nova 2 reports results on a human-verified version of the dataset.
RealKIE-FCC is a multimodal benchmark evaluating models on multimodal, document understanding, and vision tasks. LLM Stats tracks 3 models on this benchmark, scored on a 0–1 scale. The current average is 0.6, with the leader at 0.7.
Compare leaders on the best AI for multimodal, best AI for document understanding and best AI for vision leaderboards.
Current leaders
Nova 2 Pro from Amazon currently leads the RealKIE-FCC leaderboard with a score of 0.670 across 3 evaluated AI models.
Source paper
- Title
- RealKIE: Five Novel Datasets for Enterprise Key Information Extraction
- Authors
- Benjamin Townsend, Madison May, Katherine Mackowiak, Christopher Wells
- Published
- arXiv
- 2403.20101
Abstract
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/.
FAQ
Common questions about the RealKIE-FCC benchmark and leaderboard.