README.md

metadata

license: cc-by-4.0
task_categories:
  - table-question-answering
tags:
  - finance
  - xbrl
  - information-extraction
  - semantic-alignment
  - benchmark
  - thefinai
  - fintagging
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: context_index
      dtype: int64
    - name: context
      dtype: string
    - name: bio_label
      dtype: string
  splits:
    - name: test
      num_bytes: 37128330
      num_examples: 6599
  download_size: 4493992
  dataset_size: 37128330
extra_gated_heading: Request access to FinTagging BIO
extra_gated_description: >-
  FinTagging BIO is released by The Fin AI for research. Access is granted
  automatically after you complete this short form.
extra_gated_button_content: Agree and access
extra_gated_prompt: >-
  By accessing this dataset you agree to its license and to cite the FinTagging
  paper in any resulting publication.
extra_gated_fields:
  Full name: text
  Affiliation: text
  Country: country
  Intended use:
    type: select
    options:
      - Research
      - Education
      - Commercial evaluation
      - Other
  I agree to the terms above and will cite the paper: checkbox

FinTagging: An LLM-ready Benchmark for Extracting and Structuring Financial Information

📄 Paper · 🤗 Collection · 💻 Code · 🌐 The Fin AI

Part of FinTagging — FinTagging: Benchmarking LLMs for Extracting and Structuring Financial Information (arXiv:2505.20650). Formerly TheFinAI/FinTagging_BIO (the old name redirects here). A newer, larger version is available: en-fintagging-bio-v2.

FinTagging is the first full-scope, table-aware XBRL benchmark designed to evaluate the structured information extraction and semantic alignment capabilities of large language models (LLMs) in the context of XBRL-based financial reporting. It decomposes the XBRL tagging problem into two subtasks:

• FinNI: Financial entity extraction.
• FinCL: Taxonomy-driven concept alignment.

FinTagging requires models to jointly extract facts from both unstructured text and structured tables and align them with the full 10k+ US-GAAP taxonomy.

Paper | Evaluation Framework

This repository contains the original benchmark dataset without preprocessing. Annotated data (benchmark_ground_truth_pipeline.json) is provided in the "annotation" folder. For preprocessed datasets suitable for specific model architectures, please see the linked datasets in the Github README.

Datasets:

• FinNI-eval: Evaluation set for FinNI subtask.
• FinCL-eval: Evaluation set for FinCL subtask.
• FinTagging_BIO: BIO-format dataset for token-level tagging.