Triple
T20455007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylhet railway station |
E501751
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Sreemangal |
—
|
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: Sreemangal | Statement: [Sylhet railway station, connectsTo, Sreemangal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sreemangal Context triple: [Sylhet railway station, connectsTo, Sreemangal]
-
A.
Srimangal
chosen
Srimangal is a town in northeastern Bangladesh renowned for its lush tea gardens, natural beauty, and proximity to major eco-tourism sites.
-
B.
Mymensingh
Mymensingh is a historic city and district in central Bangladesh, known as an important administrative, educational, and cultural center along the Brahmaputra River.
-
C.
Sunamganj
Sunamganj is a town and district headquarters in northeastern Bangladesh, known for its wetlands, haor landscapes, and cultural ties to the Greater Sylhet region.
-
D.
Nilphamari District
Nilphamari District is an administrative district in northern Bangladesh known for its agricultural economy and location within the Rangpur region.
-
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.