Triple
T7998428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kashiwa |
E186184
|
entity |
| Predicate | neighboringMunicipality |
P17964
|
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, neighboringMunicipality, Noda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noda Context triple: [Kashiwa, neighboringMunicipality, Noda]
-
A.
Noda
chosen
Noda is a Japanese surname borne by various notable figures in politics, entertainment, and other fields.
-
B.
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.
-
C.
Omiya
Omiya is a major commercial and transportation hub in Saitama Prefecture, Japan, known for its busy railway station and urban center.
-
D.
Arima
Arima is a borough and one of the major urban centers in eastern Trinidad, known for its cultural heritage and role as a commercial hub in Trinidad and Tobago.
-
E.
Akiruno
Akiruno is a city in western Tokyo, Japan, known for its natural scenery, including rivers, forests, and hiking areas.
- 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_69ca82aaaf24819084b94d18f699ba53 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c9a12788190a5607a538f4e07c1 |
completed | March 31, 2026, 3:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbe114372c819086f06e184d5ebde2 |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 5:17 p.m.