Triple
T19205751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dwarka railway station |
E480226
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Jaipur |
—
|
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: Jaipur | Statement: [Dwarka railway station, connectsTo, Jaipur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jaipur Context triple: [Dwarka railway station, connectsTo, Jaipur]
-
A.
Jaipur
chosen
Jaipur is a major historic city in northwestern India, famed for its pink-hued architecture, royal palaces, and role as a key cultural and tourist center.
-
B.
Jodhpur
Jodhpur is a historic city in the Indian state of Rajasthan, renowned for its blue-painted old town, imposing Mehrangarh Fort, and role as a major cultural and commercial center on the edge of the Thar Desert.
-
C.
Udaipur
Udaipur is a historic town in the Indian state of Tripura, known for its ancient temples and scenic lakes.
-
D.
Udaipur
Udaipur is a town in the Lahaul and Spiti district of Himachal Pradesh, India, known for its scenic Himalayan setting and the ancient Mrikula Devi Temple.
-
E.
Udaipur
Udaipur is a historic city in India renowned for its lakes, palaces, and role as a former capital of the Mewar kingdom.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5f99cc39c81909499b8d0b78b4665 |
completed | April 20, 2026, 10:02 a.m. |
Created at: April 10, 2026, 1:18 p.m.