Triple
T35989889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tipsport Arena |
E1040813
|
entity |
| Predicate | hasSeatingCapacityForIceHockey |
P156462
|
FINISHED |
| Object | approximately 12000 |
—
|
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 12000 | Statement: [Tipsport Arena, hasSeatingCapacityForIceHockey, approximately 12000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingCapacityForIceHockey Context triple: [Tipsport Arena, hasSeatingCapacityForIceHockey, approximately 12000]
-
A.
hasIceHockeyCapacity
Indicates that an entity is capable of hosting or accommodating ice hockey activities, such as games or practices.
-
B.
iceHockeyArenaCapacity
chosen
Indicates the seating capacity or maximum number of spectators that an ice hockey arena can accommodate.
-
C.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
D.
hasLargestStandingRoomInEuropeForIceHockey
Indicates that the subject venue possesses the largest standing-room capacity in Europe specifically for ice hockey events.
-
E.
hasIceRinkDimensions
Indicates that an entity possesses or is characterized by specific ice rink measurements or size specifications.
- 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_69f76e29084c819083987b828d414de7 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0039c2d5d48190b8ef2c7ef17d8dc5 |
completed | May 10, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_6a0038e525448190a4c815f51595e78d |
completed | May 10, 2026, 7:51 a.m. |
Created at: May 3, 2026, 4:07 p.m.