Triple
T1598310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jodhpur |
E34333
|
entity |
| Predicate | distanceFromJaisalmer |
P29701
|
FINISHED |
| Object | approximately 280 km |
—
|
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 280 km | Statement: [Jodhpur, distanceFromJaisalmer, approximately 280 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromJaisalmer Context triple: [Jodhpur, distanceFromJaisalmer, approximately 280 km]
-
A.
distanceToDelhiByRoad_km
Indicates the road travel distance, measured in kilometers, from a given place to Delhi.
-
B.
distanceToGwalior
Indicates the spatial distance between a given entity and the location of Gwalior.
-
C.
distanceToDelhiByRail_km
Indicates the distance, measured in kilometers, from a given place to Delhi when traveling by rail.
-
D.
distanceFromVaranasi
Indicates the measured or specified distance between a given entity or location and the city of Varanasi.
-
E.
distanceToLucknow
Indicates the spatial distance between a given entity’s location and the city of Lucknow.
- 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_69a885fdcb9c819081ce6f0b8cd477dd |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a916d413f08190a4e137e5ed262e25 |
completed | March 5, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69a907bfb39c8190a31e0be14d3d52e6 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a916d2fae48190aaac6b2a5e31a7cf |
completed | March 5, 2026, 5:38 a.m. |
Created at: March 4, 2026, 7:27 p.m.