Triple
T13265402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kashiwa |
E315909
|
entity |
| Predicate | adjacentToMunicipality |
P33892
|
FINISHED |
| Object | Noda |
E346804
|
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: Noda | Statement: [Kashiwa, adjacentToMunicipality, Noda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noda Context triple: [Kashiwa, adjacentToMunicipality, Noda]
-
A.
Noda
chosen
Noda is a Japanese surname borne by various notable figures in politics, entertainment, and other fields.
-
B.
Ninohe
Ninohe is a small city in northeastern Japan known for its rural landscapes, traditional culture, and location within Iwate Prefecture in the Tōhoku region.
-
C.
Navashino
Navashino is a town in Nizhny Novgorod Oblast, Russia, situated on the Oka River and known as one of the endpoints of the Murom Bridge.
-
D.
Sodegaura
Sodegaura is a coastal city in Chiba Prefecture, Japan, known for its industrial waterfront, proximity to Tokyo Bay, and role within the Keiyō industrial zone.
-
E.
Omiya
Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcd4cb008190af99c4856e76ac08 |
completed | April 11, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7266665488190a4e2e411bafada85 |
completed | May 3, 2026, 10:41 a.m. |
Created at: April 9, 2026, 9:25 p.m.