Triple
T23183555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gyo Obata |
E579524
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gyo |
—
|
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: Gyo | Statement: [Gyo Obata, givenName, Gyo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gyo Context triple: [Gyo Obata, givenName, Gyo]
-
A.
Gyo
chosen
Gyo is the given name of Gyo Obata, a prominent American architect known for designing major cultural and civic buildings.
-
B.
Gyoda
Gyoda is a historic city in eastern Japan known for its ancient rice paddies, traditional tabi sock production, and preserved castle town atmosphere.
-
C.
Yakusho
Yakusho is the family name of acclaimed Japanese actor Kōji Yakusho, known for his prominent roles in both Japanese and international cinema.
-
D.
Kōgō
Kōgō is the Japanese term used to refer to the empress consort of Japan.
-
E.
Gairo
Gairo is a town and district in central Tanzania known as an agricultural hub and a key stop along the main highway between Dar es Salaam and the country’s interior.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f717d248190b2736b0789981fb2 |
completed | April 29, 2026, 4:56 a.m. |
Created at: April 17, 2026, 4:05 p.m.