Add dataset card with index as default config

README.md

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+---
+dataset_info:
+  - config_name: index
+    data_files: index.parquet
+    default: true
+  - config_name: embeddings_eng
+    data_files: embeddings_eng.parquet
+  - config_name: embeddings_fra
+    data_files: embeddings_fra.parquet
+  - config_name: embeddings_ita
+    data_files: embeddings_ita.parquet
+  - config_name: embeddings_pol
+    data_files: embeddings_pol.parquet
+  - config_name: embeddings_spa
+    data_files: embeddings_spa.parquet
+  - config_name: intervention_by_chapter
+    data_files: intervention_by_chapter.parquet
+  - config_name: intervention_summary
+    data_files: intervention_summary.parquet
+configs:
+  - config_name: index
+    data_files: index.parquet
+    default: true
+  - config_name: embeddings_eng
+    data_files: embeddings_eng.parquet
+  - config_name: embeddings_fra
+    data_files: embeddings_fra.parquet
+  - config_name: embeddings_ita
+    data_files: embeddings_ita.parquet
+  - config_name: embeddings_pol
+    data_files: embeddings_pol.parquet
+  - config_name: embeddings_spa
+    data_files: embeddings_spa.parquet
+  - config_name: intervention_by_chapter
+    data_files: intervention_by_chapter.parquet
+  - config_name: intervention_summary
+    data_files: intervention_summary.parquet
+license: cc-by-4.0
+task_categories:
+  - text-classification
+  - feature-extraction
+language:
+  - en
+  - fr
+  - it
+  - pl
+  - es
+  - grc
+tags:
+  - bible
+  - translation-studies
+  - embeddings
+  - interlinear
+pretty_name: "SIGHUM Interlinear Vector Baselines"
+size_categories:
+  - 10K<n<100K
+---
+
+# SIGHUM Interlinear Vector Baselines
+
+Companion dataset for the paper *Degree Zero of Translation: Using Interlinear Baselines to Quantify Translator Intervention* (SIGHUM 2026).
+
+## Contents
+
+| Config | Description |
+|---|---|
+| **index** (default) | Translation metadata: 79 translations across 5 languages with strategy labels |
+| embeddings_{lang} | Chapter-level Qwen3-Embedding-8B vectors (4096-dim) per translation × chapter |
+| intervention_by_chapter | L2 distance to interlinear baseline per translation × chapter |
+| intervention_summary | Per-translation summary statistics (mean, std, median distance) |
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+# Browse translations
+index = load_dataset("mrapacz/sighum-interlinear-vector-baselines", "index", split="train")
+print(index.to_pandas())
+
+# Load English chapter-level embeddings
+eng = load_dataset("mrapacz/sighum-interlinear-vector-baselines", "embeddings_eng", split="train")
+
+# Load intervention distances
+intervention = load_dataset("mrapacz/sighum-interlinear-vector-baselines", "intervention_by_chapter", split="train")
+```
+
+## Languages
+
+English (17), French (15), Italian (13), Polish (17), Spanish (17) — 74 prose translations + 5 interlinear baselines.
+
+## Model
+
+All embeddings computed with [Qwen/Qwen3-Embedding-8B](https://huggingface.co/Qwen/Qwen3-Embedding-8B).
+
+## Links
+
+- **Code & Poster**: [github.com/mrapacz/sighum-interlinear-vector-baselines](https://github.com/mrapacz/sighum-interlinear-vector-baselines)
+- **Targum Corpus**: [huggingface.co/datasets/mrapacz/targum-corpus](https://huggingface.co/datasets/mrapacz/targum-corpus)