Triple
T5880579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corel Centre |
E130737
|
entity |
| Predicate | hasTenantSport |
P31372
|
FINISHED |
| Object | ice hockey |
—
|
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: ice hockey | Statement: [Corel Centre, hasTenantSport, ice hockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTenantSport Context triple: [Corel Centre, hasTenantSport, ice hockey]
-
A.
tenantSport
chosen
Indicates that a tenant participates in or is associated with a particular sport.
-
B.
sportsTenant
Indicates that one entity occupies or uses a sports facility or venue as a tenant under some form of agreement or arrangement.
-
C.
hostsSport
Indicates that one entity provides the venue or location where a particular sport is played or conducted.
-
D.
hasSportsVenueType
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
-
E.
hasSportsGround
Indicates that an entity possesses, includes, or is associated with a sports ground or athletic field as part of its facilities or area.
- 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_69c0085523688190bfd487479ce819e6 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03fe07b7081909f8577ec3a9a1a8d |
completed | March 22, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69c0334bdc308190ad0d7199ab975588 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:57 p.m.