Triple
T14985649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chang La |
E373692
|
entity |
| Predicate | approxDistanceFromLeh |
P101567
|
FINISHED |
| Object | about 75 kilometres by road |
—
|
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: about 75 kilometres by road | Statement: [Chang La, approxDistanceFromLeh, about 75 kilometres by road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxDistanceFromLeh Context triple: [Chang La, approxDistanceFromLeh, about 75 kilometres by road]
-
A.
distanceFromLeh
chosen
Indicates the measured distance between a given location and Leh.
-
B.
distanceToDelhiApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Delhi.
-
C.
distanceToDharamshala
Indicates the spatial distance between a given entity and the location of Dharamshala.
-
D.
distanceToJodhpur
Indicates the spatial distance between a given entity or location and the city of Jodhpur.
-
E.
timeFromLehByRoad
Indicates the duration of travel required to reach a location from Leh when going by road.
- F. None of above.
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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6ff4a7c8190ab7554f3a1a09b67 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.