Triple
T16702015
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rajmachi Fort |
E405875
|
entity |
| Predicate | accessPoint |
P1985
|
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: [Rajmachi Fort, accessPoint, Lonavala]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lonavala Context triple: [Rajmachi Fort, accessPoint, 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.
Panchgani
Panchgani is a popular hill station in Maharashtra, India, known for its scenic plateau views, pleasant climate, and numerous boarding schools.
-
C.
Lohegaon
Lohegaon is a suburban area of Pune, India, known for its residential neighborhoods and proximity to key transport and defense installations.
-
D.
Amboli hill station
Amboli hill station is a scenic, high-altitude resort town in Maharashtra’s Sahyadri range, known for its cool climate, dense forests, and numerous waterfalls.
-
E.
Khandala
Khandala is a popular hill station in Maharashtra, India, known for its scenic valleys, waterfalls, and trekking spots in the Western Ghats.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e383326d7081909ef4c3b724876513 |
completed | April 18, 2026, 1:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dbf6507081909f6a49c003f9d6d6 |
completed | May 10, 2026, 7:26 p.m. |
Created at: April 10, 2026, 5:19 a.m.