Update README.md

README.md

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+pretty_name: TAFSIL
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-TAFSIL: Taxonomy Adaptable Fine-grained Entity Recognition through Distant Supervision for Indian Languages
-TAFSIL is a taxonomy-adaptable Fine-grained Entity Recognition (FgER) framework to create FgER datasets in six Indian languages. 
-TAFSIL utilizes the high interlink between the knowledge base WikiData and linked corpora Wikipedia through multi-stage heuristics and improves annotation through fuzzy match and quality sentence selection. 
-TAFSIL enables us to create datasets of a total size of around three million samples for six languages Hindi (Hi), Marathi (Mr), Sanskrit (Sa), Tamil (Ta), Telugu (Te), and Urdu (Ur) belonging to two language families Indo-European and Dravidian. 
-These six languages which are spoken by more than a billion speakers around the world.
-Utilizing the TAFSIL framework, various datasets are created in four taxonomies FIGER, OntoNotes, HAnDS, and MultiCoNER-2 for all the six languages mentioned above.
+
+# TAFSIL: Taxonomy Adaptable Fine-grained Entity Recognition through Distant Supervision for Indian Languages
+
+**TAFSIL** is a taxonomy-adaptable Fine-grained Entity Recognition (FgER) framework designed to create FgER datasets in six Indian languages: Hindi (hi), Marathi (mr), Sanskrit (sa), Tamil (ta), Telugu (te), and Urdu (ur). These languages belong to two major language families—Indo-European and Dravidian—and are spoken by over a billion people worldwide.
+
+TAFSIL leverages the high interlink between the knowledge base WikiData and linked corpora Wikipedia through multi-stage heuristics. It enhances annotation quality using fuzzy matching and quality sentence selection techniques. The framework enables the creation of datasets totaling approximately three million samples across the six languages mentioned.
+
+Utilizing the TAFSIL framework, various datasets have been created under four taxonomies: **FIGER**, **OntoNotes**, **HAnDS**, and **MultiCoNER2**.
+
+## TAFSIL Framework Overview
+
+![TAFSIL Framework Overview](TAFSIL_framework.pdf)
+
+*Figure: Overview of the TAFSIL framework.*
+
+## Dataset Statistics
+
+### TAFSIL Datasets Statistics
+
+| Taxonomy     | Language | Sentences | Entities | Tokens     |
+|--------------|----------|-----------|----------|------------|
+| **FIGER**    | Hindi    | 697,585   | 928,941  | 25,015,025 |
+|              | Marathi  | 138,114   | 193,953  | 4,010,213  |
+|              | Sanskrit | 18,946    | 25,515   | 520,970    |
+|              | Tamil    | 523,264   | 825,287  | 17,376,040 |
+|              | Telugu   | 419,933   | 616,143  | 10,103,255 |
+|              | Urdu     | 641,235   | 1,219,517| 43,556,208 |
+| **OntoNotes**| Hindi    | 699,557   | 1,177,512| 32,234,646 |
+|              | Marathi  | 138,535   | 194,317  | 4,021,660  |
+|              | Sanskrit | 19,201    | 25,459   | 520,836    |
+|              | Tamil    | 522,768   | 796,498  | 16,817,316 |
+|              | Telugu   | 420,700   | 608,041  | 9,982,017  |
+|              | Urdu     | 646,713   | 1,197,187| 42,869,948 |
+| **HAnDS**    | Hindi    | 702,941   | 1,108,130| 30,249,166 |
+|              | Marathi  | 139,163   | 195,251  | 4,039,536  |
+|              | Sanskrit | 19,294    | 25,581   | 523,540    |
+|              | Tamil    | 526,275   | 804,132  | 16,988,161 |
+|              | Telugu   | 422,736   | 611,226  | 10,034,077 |
+|              | Urdu     | 647,595   | 1,200,111| 42,988,031 |
+| **MultiCoNER2**| Hindi | 643,880   | 799,987  | 21,492,069 |
+|              | Marathi  | 125,981   | 174,861  | 3,628,450  |
+|              | Sanskrit | 17,740    | 23,372   | 479,185    |
+|              | Tamil    | 464,293   | 690,035  | 14,583,842 |
+|              | Telugu   | 392,444   | 561,088  | 9,266,603  |
+|              | Urdu     | 603,682   | 1,069,354| 38,216,564 |
+
+### TAFSIL Gold Dataset Statistics in FIGER Taxonomy
+
+| Language | Dev Entities | Dev Tokens | Test Entities | Test Tokens | IAA (κ) |
+|----------|--------------|------------|---------------|-------------|---------|
+| Hindi    | 2,910        | 20,362     | 1,578         | 11,967      | 83.34   |
+| Marathi  | 2,905        | 16,863     | 1,567         | 10,527      | 80.67   |
+| Sanskrit | 2,891        | 14,571     | 1,570         | 8,354       | 78.34   |
+| Tamil    | 2,885        | 15,334     | 1,562         | 8,961       | 76.53   |
+| Telugu   | 2,895        | 15,359     | 1,568         | 9,090       | 82.04   |
+| Urdu     | 2,710        | 21,148     | 1,511         | 12,505      | -       |
+
+### TAFSIL Gold Datasets Inter-Annotator Agreement (κ) Across Taxonomies
+
+| Taxonomy     | Hindi | Marathi | Sanskrit | Tamil | Telugu |
+|--------------|-------|---------|----------|-------|--------|
+| **FIGER**    | 83.34 | 80.67   | 78.34    | 76.53 | 82.04  |
+| **OntoNotes**| 81.41 | 78.88   | 76.98    | 75.23 | 80.24  |
+| **HAnDS**    | 83.65 | 80.03   | 77.12    | 75.63 | 81.21  |
+| **MultiCoNER2**| 84.66 | 81.84 | 79.82    | 77.89 | 83.86  |
+
+*Note: IAA (Inter-Annotator Agreement) scores are represented using Cohen's κ.*
+
+## Citation
+
+## Citation
+
+If you use this dataset, please cite the following paper:
+
+```bibtex
+@inproceedings{tafsil2025sigir,
+  author    = {Prachuryya Kaushik, Shivansh Mishra and Ashish Anand},
+  title     = {TAFSIL: Taxonomy Adaptable Fine-grained Entity Recognition through Distant Supervision for Indian Languages},
+  booktitle = {Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval},
+  year      = {2025},
+  publisher = {ACM},
+  address   = {Padua, Italy},
+  doi       = {10.1145/3726302.3730341},
+  isbn      = {979-8-4007-1592-1/2025/07}
+}