Triple
T12341458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bugulma |
E294235
|
entity |
| Predicate | administrativeCenterOf |
P383
|
FINISHED |
| Object | Bugulma District |
E983651
|
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: Bugulma District | Statement: [Bugulma, administrativeCenterOf, Bugulma District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bugulma District Context triple: [Bugulma, administrativeCenterOf, Bugulma District]
-
A.
Bugulma District
chosen
Bugulma District is an administrative and municipal district in the Republic of Tatarstan, Russia, centered around the town of Bugulma.
-
B.
Murgul District
Murgul District is an administrative district in northeastern Turkey known for its mountainous terrain and copper mining activities within Artvin Province.
-
C.
Gizab District
Gizab District is an administrative district located within Daykundi Province in central Afghanistan.
-
D.
Gizab District
Gizab District is an administrative district located within Uruzgan Province in central Afghanistan, known for its mountainous terrain and history of conflict.
-
E.
Sirkanay District
Sirkanay District is an administrative district in eastern Afghanistan known for its mountainous terrain and location near the Pakistan border.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7758dc8190bbc6a9ad00b01dce |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b8ed1dc81908a0066d7cbfda086 |
completed | May 2, 2026, 7:07 p.m. |
Created at: April 8, 2026, 9:53 p.m.