Triple
T6080367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bolpur |
E135507
|
entity |
| Predicate | connectedByRoadTo |
P11435
|
FINISHED |
| Object | Durgapur |
E165050
|
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: Durgapur | Statement: [Bolpur, connectedByRoadTo, Durgapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Durgapur Context triple: [Bolpur, connectedByRoadTo, Durgapur]
-
A.
Durgapur
chosen
Durgapur is a major industrial city in eastern India known for its steel plants and planned urban infrastructure.
-
B.
Asansol
Asansol is a major industrial and coal-mining city in eastern India, known as one of the largest urban centers in the state of West Bengal.
-
C.
Kharagpur
Kharagpur is an industrial city in eastern India best known for hosting the first campus of the Indian Institute of Technology (IIT Kharagpur) and one of the country’s longest railway platforms.
-
D.
Baranagar
Baranagar is a densely populated suburban city in the northern part of Kolkata, India, known for its industrial areas, educational institutions, and cultural heritage.
-
E.
Burdwan
Burdwan is a historic city in the Indian state of West Bengal, known for its cultural heritage, educational institutions, and former status as a major administrative and commercial center.
- 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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057735b6081908b82757505fa7d5d |
completed | March 22, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1252a178c81909a3d689ad748fb5e |
completed | March 23, 2026, 11:34 a.m. |
Created at: March 22, 2026, 4:11 p.m.