Triple
T12528619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Motobu |
E299500
|
entity |
| Predicate | subdivisionName |
P747
|
FINISHED |
| Object | Motobu |
E299500
|
NE 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: Motobu | Statement: [Motobu, subdivisionName, Motobu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Motobu Context triple: [Motobu, subdivisionName, Motobu]
-
A.
Motobu
chosen
Motobu is a town on the northern part of Okinawa Island in Japan, known for its coastal scenery, marine attractions, and role as a regional tourist destination.
-
B.
Shinya
Shinya is a Japanese given name commonly used for males.
-
C.
Munetaka
Munetaka is a Japanese professional baseball slugger best known for his record-setting home run power in Nippon Professional Baseball.
-
D.
Takaichi
Takaichi is a Japanese surname most prominently associated with conservative politician Sanae Takaichi.
-
E.
Masaru
Masaru is a Japanese given name commonly used for males and borne by various notable figures in fields such as technology, sports, and entertainment.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9545e90948190980bd4d64964a0f2 |
completed | April 10, 2026, 7:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655762ae88190ab41e23bbd65c566 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.