Datasets:
File size: 3,158 Bytes
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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)
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