Triple
T26505275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agura Waterfalls |
E669526
|
entity |
| Predicate | hasApproxDistanceFromSochiCenter |
P171403
|
FINISHED |
| Object | 10 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: 10 kilometers | Statement: [Agura Waterfalls, hasApproxDistanceFromSochiCenter, 10 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproxDistanceFromSochiCenter Context triple: [Agura Waterfalls, hasApproxDistanceFromSochiCenter, 10 kilometers]
-
A.
approximateDistanceFromSeward
Indicates the estimated spatial distance between a given entity and the location of Seward.
-
B.
hasCoordinateInCityCentreApprox
Indicates that an entity’s location is approximately within the central area of a city, based on its geographic coordinates.
-
C.
distanceFromPyeongchangOlympicPlaza
Indicates the measured distance between a given place or object and the Pyeongchang Olympic Plaza.
-
D.
distanceToSaratov_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Saratov.
-
E.
distanceFromMoscow_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and Moscow.
- 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_69eeb319ec70819090834c2591cf5f1e |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 27, 2026, 1:16 a.m.