Triple
T12118342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaipur division |
E288623
|
entity |
| Predicate | hasUrbanCenter |
P2106
|
FINISHED |
| Object | Bharatpur |
E62480
|
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: Bharatpur | Statement: [Jaipur division, hasUrbanCenter, Bharatpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bharatpur Context triple: [Jaipur division, hasUrbanCenter, Bharatpur]
-
A.
Bharatpur
chosen
Bharatpur is a historic city in eastern Rajasthan, India, known for the Keoladeo National Park, a UNESCO World Heritage-listed bird sanctuary.
-
B.
Sawai Madhopur
Sawai Madhopur is a town in Rajasthan, India, best known as the main gateway to the tiger-rich Ranthambore region and its historic fort.
-
C.
Udaipur
Udaipur is a historic city in India renowned for its lakes, palaces, and role as a former capital of the Mewar kingdom.
-
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 town in the Indian state of Tripura, known for its ancient temples and scenic lakes.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915760d208190b68f5e024b3676ba |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e46d588819086bfde1b544cab82 |
completed | May 2, 2026, 3:54 p.m. |
Created at: April 8, 2026, 9:49 p.m.