---
language:
- bo
license: other
task_categories:
- token-classification
pretty_name: Tibetan Annotation Layer Detection
tags:
- tibetan
- openpecha
- ner
- quotation
- span-detection
size_categories:
- n<1K
source_datasets:
- tsadra/OpenPecha
---

# Tibetan Annotation Layer Detection

Book-level dataset for multi-layer span detection in classical Tibetan texts (OpenPecha / tsadra). Each row is one book: raw text + cleaned character-offset spans across seven modeled annotation layers.

## Schema

| Column | Type | Description |
|---|---|---|
| `book_id` | string | OpenPecha book id (e.g. `P000010`) |
| `text` | string | Full book text (`base/v001.txt`) |
| `spans` | list of `{{start, end, label}}` | Inclusive character offsets; label is one of `QUOTATION`, `SABCHE`, `TSAWA`, `YIGCHUNG`, `CHAPTER`, `AUTHOR`, `BOOKTITLE` |
| `in_scope_layers` | list of string | Layers this book is in-scope for (absent spans are trustworthy negatives) |

Splits: `train` / `validation` / `test` (book-level stratified split; never split inside a book).

## Data quality notes

- **512 invalid spans dropped** (480 Quotation, 30 Chapter, 2 Yigchung) — all   `inverted_empty_start_eq_end_plus_1`; none recoverable.
- **Citation excluded** — only 2 books, 88% invalid.
- **Author / BookTitle** are in model scope experimentally (~1 span/book); may   be demoted to metadata-only if they underperform.
- Spans are **not** pre-combined into BIO tags — overlapping spans are preserved   at full fidelity; priority resolution happens at training time.