Triple
T4149979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magarpatta City |
E89879
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Pune |
E14838
|
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: Pune | Statement: [Magarpatta City, locatedIn, Pune]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pune Context triple: [Magarpatta City, locatedIn, Pune]
-
A.
Pune
chosen
Pune is a major cultural, educational, and IT hub in the western Indian state of Maharashtra, known for its universities, historical significance, and rapidly growing urban economy.
-
B.
Nagpur
Nagpur is a major city in the Indian state of Maharashtra, known as a key political and commercial center and often referred to as the "Orange City" for its famous orange production.
-
C.
Nashik
Nashik is a historic city in the Indian state of Maharashtra, known for its religious significance in Hinduism and as a major center of wine production.
-
D.
Pune Metropolitan Region
Pune Metropolitan Region is a major urban and industrial agglomeration in western India centered on the city of Pune, known for its rapidly growing IT, manufacturing, and educational hubs.
-
E.
Vadodara
Vadodara is a major city in western India known for its rich cultural heritage, educational institutions, and industrial development.
- 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_69aed95a59a881909b26e70b42c6811a |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0273a038819087db092da234e767 |
completed | March 9, 2026, 5:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bb60e9709881909673b8980694902b |
completed | March 19, 2026, 2:35 a.m. |
Created at: March 9, 2026, 3:43 p.m.