Consolidated Receipt Dataset for Post-OCR Parsing
OCR is inevitably linked to NLP since its final output is in text. Advances in document intelligence are driving the need for a unified technology that integrates OCR with various NLP tasks, especially semantic parsing. Since OCR and semantic parsing have been studied as separate tasks so far, the datasets for each task on their own are rich, while those for the integrated post-OCR parsing tasks are relatively insufficient. In this study, we publish a consolidated dataset for receipt parsing as the first step towards post-OCR parsing tasks. The dataset consists of thousands of Indonesian receipts, which contains images and box/text annotations for OCR, and multi-level semantic labels for parsing. The proposed dataset can be used to address various OCR and parsing tasks.
Variants: CORD
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Key Information Extraction | RORE (GeoLayoutLM) | Modeling Layout Reading Order as … | 2024-09-29 |
| Key Information Extraction | TPP (LayoutMask) | Reading Order Matters: Information Extraction … | 2023-10-17 |
| Key Information Extraction | LayoutMask (base) | LayoutMask: Enhance Text-Layout Interaction in … | 2023-05-30 |
| Key Information Extraction | LayoutMask (large) | LayoutMask: Enhance Text-Layout Interaction in … | 2023-05-30 |
| Key Information Extraction | GeoLayoutLM | GeoLayoutLM: Geometric Pre-training for Visual … | 2023-04-21 |
| Key Information Extraction | LayoutLMv3 Large | LayoutLMv3: Pre-training for Document AI … | 2022-04-18 |
| Key Information Extraction | LILT | LiLT: A Simple yet Effective … | 2022-02-28 |
| Key Information Extraction | LayoutLMv2LARGE | LayoutLMv2: Multi-modal Pre-training for Visually-Rich … | 2020-12-29 |
| Key Information Extraction | LayoutLMv2BASE | LayoutLMv2: Multi-modal Pre-training for Visually-Rich … | 2020-12-29 |
Recent papers with results on this dataset: