Triple
T22282107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magura District |
E550758
|
entity |
| Predicate | hasVehicleRegistrationCode |
P1173
|
FINISHED |
| Object | Magura |
—
|
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: Magura | Statement: [Magura District, hasVehicleRegistrationCode, Magura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magura Context triple: [Magura District, hasVehicleRegistrationCode, Magura]
-
A.
Magura
chosen
Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
-
B.
Magura
Magura is a mountain peak in the Kysucké Beskydy range of northern Slovakia, known for its forested slopes and scenic hiking routes.
-
C.
Koyo
Koyo is a well-known Japanese brand of bearings and automotive components owned by JTEKT Corporation.
-
D.
Mibuchi
Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
-
E.
Miura
Miura is a coastal city on the Miura Peninsula in Kanagawa Prefecture, Japan, known for its fishing industry, beaches, and scenic ocean views.
- 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_69e11e44d538819097c6b8f333af3352 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f14eac0994819088e39a1b5d39cf18 |
completed | April 29, 2026, 12:19 a.m. |
Created at: April 16, 2026, 8:40 p.m.