license: cc-by-sa-3.0
language:
- ja
- en
task_categories:
- translation
- token-classification
tags:
- japanese
- reading-comprehension
- furigana
- grammar
- annotation
- distillation
pretty_name: Kanjiland Silver Annotations
size_categories:
- 1K<n<10K
Kanjiland — Silver Annotations
9,388 Japanese sentences annotated in the full Kanjiland reading-comprehension format: morpheme segmentation, furigana (ruby on kanji runs), per-token contextual glosses, word groupings, an English sentence translation, and grammar-pattern labels from a closed 120-rule inventory.
Part of Kanjiland, a from-scratch Japanese reading-comprehension engine.
Format
Each line of silver_annotations.jsonl is:
{"ja": "<Japanese sentence>", "wire": "<tagged annotation string>"}
The wire string uses Unicode Private-Use-Area separators (⟨T⟩ token, ⟨W⟩ word,
⟨S⟩ sentence, ⟨G⟩ grammar). The format is specified in
docs/FORMAT_SPEC.md;
the grammar rule inventory is
docs/GRAMMAR_RULES.md.
How it was made (hybrid supervision)
- Source sentences: KFTT (Kyoto Free Translation Task), formal/Wikipedia domain.
- Deterministic layer: MeCab + UniDic (offline) — segmentation, kanji-run ruby, POS, lemma.
- Judgment layer: an OpenAI teacher model — contextual glosses, translation, grammar labels.
- Gate: every annotation passes a strict format linter (93.9% of 10,000 sentences passed).
License & attribution
CC-BY-SA 3.0. Derived from KFTT (© Graham Neubig, CC-BY-SA 3.0,
http://www.phontron.com/kftt/) — attribute KFTT and this project, and share
derivatives alike. English glosses/translations are model-generated (OpenAI);
deterministic labels use MeCab (BSD) + UniDic. See the repo NOTICE.md.
Limitations
- Domain: formal/Wikipedia (KFTT) — not conversational or web Japanese.
- Silver, not gold: teacher-generated; the linter catches structural errors but not every semantic mislabel. Spot-audited, not exhaustively verified.