Triple
T14026299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanatal |
E337464
|
entity |
| Predicate | distanceFromMussoorie_km |
P112530
|
FINISHED |
| Object | approximately 40 |
—
|
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 40 | Statement: [Kanatal, distanceFromMussoorie_km, approximately 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMussoorie_km Context triple: [Kanatal, distanceFromMussoorie_km, approximately 40]
-
A.
distanceFromShimla_km
Indicates the physical distance, measured in kilometers, between a given place and Shimla.
-
B.
distanceToDehradun
Indicates the spatial distance between an entity’s location and the city of Dehradun.
-
C.
distanceFromAlmora
Indicates the measured distance between a given location or entity and the place Almora.
-
D.
distanceToSrinagar_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Srinagar.
-
E.
distanceFromMunnar
Indicates the spatial distance measured from the reference location Munnar to another place or entity.
- 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_69d81c6543a48190bd5ba93d7419e797 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2fa6ca7481908976ce748a1957b1 |
completed | April 14, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_69de05ab36b48190920efb1869bdb1fe |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239524688190a0f2408c239cfcaa |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.