Improve dataset card: Add metadata and description

README.md

@@ -1,21 +1,29 @@
 ---
-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
-configs:
-- config_name: default
-  data_files:
-  - split: test
-    path: data/test-*
+license: cc-by-nc-4.0
+task_categories:
+- table-question-answering
+tags:
+- finance
+- xbrl
+- information-extraction
+- semantic-alignment
 ---
+
+# FinTagging: An LLM-ready Benchmark for Extracting and Structuring Financial Information
+
+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](https://huggingface.co/papers/2505.20650) | [Evaluation Framework](https://github.com/The-FinAI/FinBen)
+
+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.