Triple
T1335010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kojiki |
E28726
|
entity |
| Predicate | hasModernTranslationsIn |
P2303
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Kojiki, hasModernTranslationsIn, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModernTranslationsIn Context triple: [Kojiki, hasModernTranslationsIn, English]
-
A.
hasTranslation
chosen
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
notableModernTranslation
Indicates that one entity is a modern translation of another that is considered especially significant or noteworthy.
-
C.
hasModernEditions
Indicates that an original work or text has one or more updated or contemporary published editions.
-
D.
hasModernName
Indicates that an entity is associated with its current or contemporary name, as opposed to an older or historical one.
-
E.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1eb119881909dd5fbf728d9e8ba |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:55 p.m.