Triple
T20455014
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylhet railway station |
E501751
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Chandpur |
—
|
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: Chandpur | Statement: [Sylhet railway station, connectsTo, Chandpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chandpur Context triple: [Sylhet railway station, connectsTo, Chandpur]
-
A.
Chandpur District
chosen
Chandpur District is a riverine administrative region in eastern Bangladesh known for its strategic location at major river confluences and its prominence in fishing and agriculture.
-
B.
Faridpur
Faridpur is a historic town in central Bangladesh known for its cultural heritage and role in the Bengal Renaissance.
-
C.
Kishoreganj
Kishoreganj is a town and district headquarters in central Bangladesh known for its agricultural economy, riverine landscape, and cultural heritage.
-
D.
Comilla
Comilla is a major city in eastern Bangladesh known for its historical sites, educational institutions, and role as a regional commercial hub.
-
E.
Chapainawabganj
Chapainawabganj is a district town in western Bangladesh known for its mango production and location near the border with India.
- 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.