Triple
T28347209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otogizōshi |
E717985
|
entity |
| Predicate | hasTitleInJapaneseScript |
P28734
|
FINISHED |
| Object | お伽草紙 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: お伽草紙 | Statement: [Otogizōshi, hasTitleInJapaneseScript, お伽草紙]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleInJapaneseScript Context triple: [Otogizōshi, hasTitleInJapaneseScript, お伽草紙]
-
A.
hasTitleInRevisedRomanization
Indicates that an entity has a specific title expressed using the Revised Romanization system for Korean.
-
B.
titleInJapanese
Indicates that one entity is the title of another entity expressed specifically in the Japanese language.
-
C.
hasTitleInTransliteration
Indicates that an entity has a specific title represented in a transliterated form from another writing system.
-
D.
hasNameInJapanese
chosen
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
E.
hasTitleInEnglishOrthography
Indicates that an entity has a specific title expressed using English spelling and writing conventions.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f7221dc9a88190bb8194fcc29c42bc |
completed | May 3, 2026, 10:23 a.m. |
| PD | Predicate disambiguation | batch_69f72153a9188190b02adc84e1be4af8 |
completed | May 3, 2026, 10:20 a.m. |
Created at: April 28, 2026, 12:44 a.m.