Triple
T12832341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Triangle tourist circuit |
E306818
|
entity |
| Predicate | approxDistanceDelhiToAgra |
P42970
|
FINISHED |
| Object | about 200 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: about 200 km | Statement: [Golden Triangle tourist circuit, approxDistanceDelhiToAgra, about 200 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approxDistanceDelhiToAgra Context triple: [Golden Triangle tourist circuit, approxDistanceDelhiToAgra, about 200 km]
-
A.
distanceFromAgra
Indicates the spatial distance between a given entity or location and the city of Agra.
-
B.
distanceToDelhiApproxKm
chosen
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Delhi.
-
C.
distanceToDelhiByRail_km
Indicates the distance, measured in kilometers, from a given place to Delhi when traveling by rail.
-
D.
distanceToDelhiByRoad_km
Indicates the road travel distance, measured in kilometers, from a given place to Delhi.
-
E.
distanceFromAurangabad
Indicates the measured spatial distance between a given location and Aurangabad.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:34 p.m.