Triple
T3876588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khandala |
E92515
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Lonavala |
E91226
|
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: Lonavala | Statement: [Khandala, near, Lonavala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lonavala Context triple: [Khandala, near, Lonavala]
-
A.
Lonavala
chosen
Lonavala is a popular hill station in Maharashtra, India, known for its lush green valleys, waterfalls, and scenic views along the Mumbai–Pune route.
-
B.
Khandala
Khandala is a popular hill station in Maharashtra, India, known for its scenic valleys, waterfalls, and trekking spots in the Western Ghats.
-
C.
Virajpet
Virajpet is a town in the Kodagu (Coorg) district of Karnataka, India, known as a gateway to the scenic Brahmagiri Hills and surrounding Western Ghats.
-
D.
Ratnagiri
Ratnagiri is a coastal city in Maharashtra, India, known for its Alphonso mangoes, historic forts, and scenic beaches along the Konkan coast.
-
E.
Nagole
Nagole is a residential and commercial neighborhood in Hyderabad, India, served as a key terminus and transit hub on the Hyderabad Metro network.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec719c148190a731773ac262221b |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51251609c81909e19132475eb612d |
completed | March 14, 2026, 7:46 a.m. |
Created at: March 9, 2026, 3:20 p.m.