Triple
T22036785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayfield Toyota Ice Palace |
E544230
|
entity |
| Predicate | hasRinkType |
P18571
|
FINISHED |
| Object | full-sized ice rink |
—
|
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: full-sized ice rink | Statement: [Mayfield Toyota Ice Palace, hasRinkType, full-sized ice rink]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRinkType Context triple: [Mayfield Toyota Ice Palace, hasRinkType, full-sized ice rink]
-
A.
hasRinkCount
Indicates the number of ice rinks associated with or contained within a given entity.
-
B.
playsOnRinkType
Indicates that an entity participates in a game or activity on a specific type of rink surface or rink configuration.
-
C.
iceRinkType
chosen
Indicates the specific kind or category of an ice rink associated with an entity (e.g., indoor, outdoor, Olympic-sized).
-
D.
hasBenchType
Indicates that an entity is associated with or characterized by a specific type or category of bench.
-
E.
hasIceRinks
Indicates that an entity possesses, contains, or provides access to one or more ice rinks.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f1f95c8190a324c84313cd91ee |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
Created at: April 16, 2026, 8:25 p.m.