Triple
T1569475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bengal Sultanate |
E33505
|
entity |
| Predicate | notableCity |
P2813
|
FINISHED |
| Object | Sylhet |
E117161
|
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: Sylhet | Statement: [Bengal Sultanate, notableCity, Sylhet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sylhet Context triple: [Bengal Sultanate, notableCity, Sylhet]
-
A.
Sylhet
chosen
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.
-
B.
Barisal
Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
-
C.
Mymensingh
Mymensingh is a historic city and district in central Bangladesh, known as an important administrative, educational, and cultural center along the Brahmaputra River.
-
D.
Rajshahi
Rajshahi is a prominent city in western Bangladesh, known as an important cultural, educational, and commercial center of the Bengal region.
-
E.
Noakhali
Noakhali is a coastal district in southeastern Bangladesh, historically part of the Bengal region and known for its agrarian economy and vulnerability to cyclones and river erosion.
- 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908b67304819081ad555000e51197 |
completed | March 5, 2026, 4:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adbf3d408881909688667be4a32931 |
completed | March 8, 2026, 6:26 p.m. |
Created at: March 4, 2026, 7:27 p.m.