Triple
T528037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lysgårdsbakken |
E10966
|
entity |
| Predicate | hasSpectatorCapacity |
P2491
|
FINISHED |
| Object | approximately 35,000 |
—
|
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 35,000 | Statement: [Lysgårdsbakken, hasSpectatorCapacity, approximately 35,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpectatorCapacity Context triple: [Lysgårdsbakken, hasSpectatorCapacity, approximately 35,000]
-
A.
hasSpectatorArea
Indicates that a location or facility includes a designated area intended for spectators to observe an event or activity.
-
B.
seatingCapacity
chosen
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
C.
hasAudienceSize
Indicates the relationship between an entity and the number of people or size of group that receives, views, or engages with it.
-
D.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
E.
hasReservedSeats
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
- 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.