Triple
T26626332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onekotan Island |
E668358
|
entity |
| Predicate | formerJapaneseName |
P153456
|
FINISHED |
| Object | Onnekotan-tō |
—
|
NE NERFINISHED |
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: Onnekotan-tō | Statement: [Onekotan Island, formerJapaneseName, Onnekotan-tō]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerJapaneseName Context triple: [Onekotan Island, formerJapaneseName, Onnekotan-tō]
-
A.
formerJapaneseNameOf
chosen
Indicates that one entity was previously used as the Japanese name for another entity but is no longer its current Japanese name.
-
B.
JapaneseNameOrigin
Indicates that one entity’s name originates from or is derived from the Japanese language or naming tradition in relation to another entity.
-
C.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
-
D.
JapaneseForceName
Indicates that an entity is known by a name used for a Japanese military or armed force.
-
E.
nameInMcCuneReischauer
Indicates that an entity’s name is represented using the McCune–Reischauer romanization system.
- 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_69ee9cff507c819092b95bf7219a702e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: April 27, 2026, 2:23 a.m.