Triple
T22646143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muktabai |
E558967
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Pandharpur |
—
|
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: Pandharpur | Statement: [Muktabai, associatedWith, Pandharpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pandharpur Context triple: [Muktabai, associatedWith, Pandharpur]
-
A.
Pandharpur
chosen
Pandharpur is a major pilgrimage town in Maharashtra, India, renowned for its Vitthal (Vithoba) temple and its central role in the Bhakti movement.
-
B.
Shirdi
Shirdi is a prominent pilgrimage town in Maharashtra, India, best known as the home and shrine of the revered saint Sai Baba.
-
C.
Mahadevapura
Mahadevapura is a rapidly developing residential and commercial neighborhood in eastern Bengaluru, India, known for its proximity to major IT parks and tech hubs.
-
D.
Vithalwadi
Vithalwadi is a suburban railway station in the Mumbai metropolitan area that serves local commuters on the Central Line.
-
E.
Bhawanipatna
Bhawanipatna is a town in the Indian state of Odisha known as an administrative and commercial center of the Kalahandi region.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f170371fe08190a6a53809d185f8b5 |
completed | April 29, 2026, 2:43 a.m. |
Created at: April 17, 2026, 3:05 p.m.