Triple
T17953493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rangpur culture |
E448888
|
entity |
| Predicate | hasSite |
P1205
|
FINISHED |
| Object | Rangpur |
—
|
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: Rangpur | Statement: [Rangpur culture, hasSite, Rangpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rangpur Context triple: [Rangpur culture, hasSite, Rangpur]
-
A.
Rangpur
chosen
Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
-
B.
Chittagong
Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
-
C.
Sylhet
Sylhet is a historically and culturally significant city and region in northeastern Bangladesh, known for its tea gardens, lush landscapes, and role as a major economic and spiritual center.
-
D.
Barisal
Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
-
E.
Comilla
Comilla is a major city in eastern Bangladesh known for its historical sites, educational institutions, and role as a regional commercial hub.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afae2aa081909a59a8cd4f1d04e1 |
completed | April 19, 2026, 10:34 a.m. |
Created at: April 10, 2026, 10:21 a.m.