Triple
T21495842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanai |
E530349
|
entity |
| Predicate | mergerPartnerOf |
P6600
|
FINISHED |
| Object | Hatano |
—
|
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: Hatano | Statement: [Kanai, mergerPartnerOf, Hatano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hatano Context triple: [Kanai, mergerPartnerOf, Hatano]
-
A.
Hatano
chosen
Hatano was a former municipality in Niigata Prefecture, Japan, that was incorporated into the city of Sado through a merger.
-
B.
Hatogaya
Hatogaya was a former city in Saitama Prefecture, Japan, that became part of the expanded city of Kawaguchi.
-
C.
Hatagaya
Hatagaya is a residential neighborhood in Tokyo known for its convenient access to central Shibuya and its mix of quiet local streets and urban amenities.
-
D.
Hayakita
Hayakita is a town in Hokkaido, Japan, known as a small rural community situated near the city of Sapporo.
-
E.
Hiranaka
Hiranaka is a Japanese surname borne by individuals such as former professional boxer Akinobu Hiranaka.
- 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_69e0c45bd15481909fba5910765cdda2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea582d9c8190b95ff6e1b8179b81 |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:23 p.m.