Triple
T12818727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pamporovo |
E306470
|
entity |
| Predicate | hasTotalPisteLength |
P77354
|
FINISHED |
| Object | approximately 30 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: approximately 30 kilometers | Statement: [Pamporovo, hasTotalPisteLength, approximately 30 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTotalPisteLength Context triple: [Pamporovo, hasTotalPisteLength, approximately 30 kilometers]
-
A.
hasSkiRunsLength_km
chosen
Indicates the total length, in kilometers, of the ski runs associated with an entity.
-
B.
hasPisteType
Indicates that an entity (such as a ski run or trail) is associated with a specific type or category of piste.
-
C.
tourLength
Indicates the total duration or distance covered by a tour or route.
-
D.
trackLengthApproxKm
Indicates that one entity has an approximate track length, measured in kilometers, associated with it.
-
E.
totalRouteLength
Indicates the overall distance or length of an entire route when all its segments are combined.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9d00088190ac0f5d60e1de7a7c |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d964100f7481909a197396003d4a71 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:31 p.m.