Triple
T20455002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylhet railway station |
E501751
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Chittagong |
—
|
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: Chittagong | Statement: [Sylhet railway station, connectsTo, Chittagong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chittagong Context triple: [Sylhet railway station, connectsTo, Chittagong]
-
A.
Chittagong
chosen
Chittagong is a major coastal city and Bangladesh’s principal seaport, known for its bustling maritime trade and industrial significance.
-
B.
Rangpur
Rangpur is a city in northern Bangladesh known as a regional administrative, cultural, and commercial center.
-
C.
Barisal
Barisal is a major city in southern Bangladesh, historically known as a cultural and riverine hub of the Bengal region.
-
D.
Dhaka
Dhaka is the capital and largest city of Bangladesh, serving as the country’s political, economic, and cultural center.
-
E.
Dhaka
Dhaka is a town in the East Champaran district of Bihar, India, known as a local administrative and commercial center in the region.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a0dd188190ab6cbb387d9c0c1d |
completed | April 20, 2026, 9:12 p.m. |
Created at: April 16, 2026, 11:32 a.m.