Triple
T22703363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpensia Biathlon Centre |
E561379
|
entity |
| Predicate | hasShootingRange |
P122309
|
FINISHED |
| Object | biathlon rifle range |
—
|
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: biathlon rifle range | Statement: [Alpensia Biathlon Centre, hasShootingRange, biathlon rifle range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShootingRange Context triple: [Alpensia Biathlon Centre, hasShootingRange, biathlon rifle range]
-
A.
shootingRange
chosen
Indicates that one entity serves as a location or facility where another entity engages in shooting activities, typically for practice or training.
-
B.
hasShootingPosition
Indicates that an entity has a designated location or spot from which shooting (e.g., firing a weapon or taking a shot) is performed.
-
C.
hasShootingLocation
Indicates that an audiovisual work was filmed or recorded at a particular location.
-
D.
typicalShootingDistances
Indicates the usual or standard distances at which shooting (e.g., with a weapon or camera) typically occurs in a given context.
-
E.
hasCannon
Indicates that one entity is equipped with, contains, or features a cannon.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178cca1e48190bbe7910f13692803 |
completed | April 29, 2026, 3:19 a.m. |
| PD | Predicate disambiguation | batch_69ee62bd657c81909f7b01245b080a5f |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:16 p.m.