Triple
T16702156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pawna Lake |
E405878
|
entity |
| Predicate | distanceFromLonavala |
P124293
|
FINISHED |
| Object | approximately 20 kilometers |
—
|
LITERAL 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: approximately 20 kilometers | Statement: [Pawna Lake, distanceFromLonavala, approximately 20 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLonavala Context triple: [Pawna Lake, distanceFromLonavala, approximately 20 kilometers]
-
A.
distanceFromPune
Indicates the spatial distance between a given location or entity and the city of Pune.
-
B.
distanceFromBengaluru
Indicates the measured spatial distance between a given entity’s location and the city of Bengaluru.
-
C.
distanceFromNashik
Indicates the spatial distance between a given entity or location and the city of Nashik.
-
D.
distanceFromVrindavan
Indicates the spatial distance between a given entity and the location Vrindavan.
-
E.
distanceFromBangalore
Indicates the spatial distance separating a given entity or location from Bangalore.
- F. None of above. chosen
Provenance (4 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. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
| PDg | Predicate description generation | batch_69e326b9e84881909a9166e65bd850d6 |
completed | April 18, 2026, 6:37 a.m. |
Created at: April 10, 2026, 5:19 a.m.