mlsanityData to 14 Oct 2026

KPI-EDGAR: A Novel Dataset and Accompanying Metric for Relation Extraction from Financial Documents

arXiv 2210.09163 ↗First posted 17 Oct 2022cs.CLcited by 9

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Abstract (arXiv)

We introduce KPI-EDGAR, a novel dataset for Joint Named Entity Recognition and Relation Extraction building on financial reports uploaded to the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system, where the main objective is to extract Key Performance Indicators (KPIs) from financial documents and link them to their numerical values and other attributes. We further provide four accompanying baselines for benchmarking potential future research. Additionally, we propose a new way of measuring the success of said extraction process by incorporating a word-level weighting scheme into the conventional F1 score to better model the inherently fuzzy borders of the entity pairs of a relation in this domain.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 19 of its 46 references that are in the map. First posted on arXiv 17 Oct 2022.

Builds on

19 of 46 references.

References · 19

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  4. 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,304
  5. 2019Span-based Joint Entity and Relation Extraction with Transformer Pre-trainingcited by 133
  6. 2020BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervisioncited by 91
  7. 2020Double Graph Based Reasoning for Document-level Relation Extractioncited by 87
  8. 2020Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoderscited by 87
  9. 2020Automated Concatenation of Embeddings for Structured Predictioncited by 86
  10. 2021Document-level Relation Extraction as Semantic Segmentationcited by 80
  11. 2021Improving Named Entity Recognition by External Context Retrieving and Cooperative Learningcited by 76
  12. 2021Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extractioncited by 68
7 more
  1. 2020A Frustratingly Easy Approach for Entity and Relation Extractioncited by 37
  2. 2022T-NER: An All-Round Python Library for Transformer-based Named Entity Recognitioncited by 37
  3. 2021EDGAR-CORPUS: Billions of Tokens Make The World Go Roundcited by 32
  4. 2020Interpretable Multi-dataset Evaluation for Named Entity Recognitioncited by 27
  5. 2021A Trigger-Sense Memory Flow Framework for Joint Entity and Relation Extractioncited by 26
  6. 2022KPI-BERT: A Joint Named Entity Recognition and Relation Extraction Model for Financial Reportscited by 19
  7. 2020Constrained Decoding for Computationally Efficient Named Entity Recognition Taggerscited by 8

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 1; 2025: 3; 2026: 1.

9 papers.

  1. 2023A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontierscited by 22
  2. 2023Improving Zero-Shot Text Matching for Financial Auditing with Large Language Modelscited by 5
  3. 2023Self-Specialization: Uncovering Latent Expertise within Large Language Modelscited by 5
  4. 2024Enterprise Benchmarks for Large Language Model Evaluationcited by 5
  5. 2025HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filingscited by 1
  6. 2026CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Basescited by 1
  7. 2023Controlled Randomness Improves the Performance of Transformer Modelscited by 0
  8. 2025An Automated LLM-based Pipeline for Asset-Level Database Creation to Assess Deforestation Impactcited by 0
  9. 2025A Pluggable Multi-Task Learning Framework for Sentiment-Aware Financial Relation Extractioncited by 0