Triple
T528156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nordic combined |
E10968
|
entity |
| Predicate | crossCountryDistance |
P7750
|
FINISHED |
| Object | 10 km in standard individual event |
—
|
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 km in standard individual event | Statement: [Nordic combined, crossCountryDistance, 10 km in standard individual event]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crossCountryDistance Context triple: [Nordic combined, crossCountryDistance, 10 km in standard individual event]
-
A.
distance
chosen
Indicates the spatial separation or length between two points, objects, or locations.
-
B.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
C.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
D.
distanceCategory
Indicates the qualitative classification of how far apart two entities are from each other (e.g., near, medium, far).
-
E.
crossesMountainRange
Indicates that one entity traverses from one side of a mountain range to the other, passing through or over it.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1d2851c81908129f7da932ab7b3 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f01ac3ec8190a94a05955532c7fa |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.