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README.md

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----
-license: mit
----
+---
+language:
+- ta
+license: cc-by-sa-4.0
+task_categories:
+- text-generation
+tags:
+- tamil
+- morphology
+- benchmark
+- evaluation
+- linguistics
+- dravidian
+- agglutinative
+pretty_name: "Tamil Morphological Generalization Benchmark"
+size_categories:
+- 1K<n<10K
+---
+
+# Tamil Morphological Generalization Benchmark (TAMIL-MORPH)
+
+**The first morphological generalization benchmark for Tamil** -- 1,030 test cases across 9 categories designed to evaluate whether LLMs truly understand Tamil morphological rules or merely memorize surface forms.
+
+**Paper:** *"A Thousand Language Problem: Morphological Understanding in Linguistic AI"*
+
+## Benchmark Overview
+
+| Category | Test Cases | Description |
+|----------|-----------|-------------|
+| Case Suffixes (வேற்றுமை) | 240 | 6 grammatical cases across 40 noun roots |
+| Plural + Case (பன்மை) | ~160 | Plural formation with case markers |
+| Verb Conjugation (வினைத்திரிபு) | ~210 | 7 person-tense combinations across verb roots |
+| Sandhi (புணர்ச்சி) | ~50 | Sound changes at word boundaries |
+| Honorific Forms (மரியாதை) | ~90 | Informal/formal/high-respect registers |
+| Negation (எதிர்மறை) | ~90 | Present/past/future negative forms |
+| Compound Words (கூட்டுச்சொல்) | ~50 | Word joining rules |
+| Conditional/Causal (நிபந்தனை) | ~60 | Conditional and causal suffixes |
+| Novel Combinations (புதிய வடிவங்கள்) | ~80 | Multi-suffix forms never seen in training |
+| **Total** | **1,030** | |
+
+## Baseline Results
+
+| Model | Overall Accuracy |
+|-------|-----------------|
+| GPT-4o-mini | 54.0% |
+
+## Files
+
+- `Benchmarkdata.md` -- Full benchmark data (JSON arrays in Markdown)
+- `morph_benchmark_eval.py` -- Complete evaluation script (supports local HF models, OpenAI, Google Gemini backends)
+- `baselines/gpt-4o-mini_results.json` -- Detailed per-test results for GPT-4o-mini
+- `kaggle_benchmark.ipynb` -- Ready-to-run Kaggle notebook for benchmarking
+- `runpod_benchmark.py` -- RunPod GPU benchmarking script
+
+## Usage
+
+### Run evaluation locally
+
+```bash
+# With OpenAI API
+python morph_benchmark_eval.py --model gpt-4o-mini --backend openai
+
+# With Google Gemini (free tier)
+python morph_benchmark_eval.py --model gemini-2.0-flash --backend gemini
+
+# With local HuggingFace model
+python morph_benchmark_eval.py --model Tamil-ai/tamil-qwen25-7b-instruct --backend local
+
+# Run all configured models
+python morph_benchmark_eval.py --all
+```
+
+### Load benchmark data programmatically
+
+```python
+from huggingface_hub import hf_hub_download
+import json, re
+from pathlib import Path
+
+path = hf_hub_download(
+    repo_id="Tamil-ai/tamil-morphological-benchmark",
+    filename="Benchmarkdata.md",
+    repo_type="dataset",
+)
+# Parse JSON blocks from the markdown (see morph_benchmark_eval.py for full parser)
+```
+
+## Data Format
+
+Each category contains structured JSON with roots, meanings, and expected morphological forms:
+
+```json
+{
+  "root": "வீடு",
+  "root_meaning": "house",
+  "forms": {
+    "accusative": {"tamil": "வீட்டை", "meaning": "the house (object)"},
+    "dative": {"tamil": "வீட்டுக்கு", "meaning": "to the house"},
+    "locative": {"tamil": "வீட்டில்", "meaning": "in the house"}
+  }
+}
+```
+
+## Scoring
+
+- **1.0** -- Exact match (after Tamil text normalization)
+- **0.5** -- Partial match (predicted is substring of expected)
+- **0.0** -- Wrong
+
+## Why This Benchmark?
+
+Existing Tamil NLP benchmarks test translation or classification. None test whether models understand the **generative morphological rules** of Tamil -- an agglutinative language where a single root can produce hundreds of valid surface forms through suffix combinations.
+
+This benchmark is transferable to other agglutinative languages (Turkish, Finnish, Hungarian, Korean, etc.) by replacing the morphological rules.
+
+## Validation
+
+All 1,030 test cases were validated using:
+1. Finite State Transducer (FST) analysis
+2. Stanza NLP morphological parser
+3. Manual rule verification
+
+## Citation
+
+```bibtex
+@misc{tamilmorph2026,
+  title={A Thousand Language Problem: Morphological Understanding in Linguistic AI},
+  author={Tamil-AI},
+  year={2026},
+  publisher={HuggingFace},
+  url={https://huggingface.co/datasets/Tamil-ai/tamil-morphological-benchmark}
+}
+```