Triple
T16070973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Highway 9 (India) |
E389858
|
entity |
| Predicate | connectsCity |
P4245
|
FINISHED |
| Object | Rudrapur |
E1026798
|
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: Rudrapur | Statement: [National Highway 9 (India), connectsCity, Rudrapur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rudrapur Context triple: [National Highway 9 (India), connectsCity, Rudrapur]
-
A.
Rudrapur
chosen
Rudrapur is a rapidly developing industrial and commercial city in the Udham Singh Nagar district of Uttarakhand, India.
-
B.
Rudrapur
Rudrapur is a town in the Indian state of Uttar Pradesh, known as a local commercial and agricultural center in the region.
-
C.
Mukteshwar
Mukteshwar is a scenic hill town in Uttarakhand, India, known for its panoramic Himalayan views, fruit orchards, and tranquil forests.
-
D.
Nalhati
Nalhati is a town in the Birbhum district of West Bengal, India, known for its religious significance and regional marketplace.
-
E.
Ambarnath
Ambarnath is a suburban city in the Thane district of Maharashtra, India, known for its historic Shiva temple and its role as a residential and industrial hub near Mumbai.
- 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_69d86daf32ec8190a8c0466c8f49c3c0 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183be909c8190ac6c37ab047151ae |
completed | April 17, 2026, 12:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe4827cd48190aa470c6537e72508 |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 10, 2026, 4:57 a.m.