Triple
T15850586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utsunomiya Brex |
E384325
|
entity |
| Predicate | homeCity |
P263
|
FINISHED |
| Object | Utsunomiya |
—
|
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: Utsunomiya | Statement: [Utsunomiya Brex, homeCity, Utsunomiya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Utsunomiya Context triple: [Utsunomiya Brex, homeCity, Utsunomiya]
-
A.
Utsunomiya
chosen
Utsunomiya is a city in Tochigi Prefecture, Japan, known as a regional commercial center and for its specialty gyoza (dumplings).
-
B.
Kōriyama
Kōriyama is a major commercial and transportation hub city located in Japan’s Tōhoku region.
-
C.
Matsudo
Matsudo is a city in Chiba Prefecture, Japan, located in the Greater Tokyo Area and functioning largely as a residential and commercial suburb of Tokyo.
-
D.
Omiya
Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
-
E.
Omiya
Omiya is a neighborhood within Tokyo’s Suginami ward, known as a primarily residential area with local shops and community facilities.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e14cab0fe48190bd6629e071761e91 |
completed | April 16, 2026, 8:55 p.m. |
Created at: April 10, 2026, 4:50 a.m.