Triple
T824207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Campus (Queen's University) |
E17816
|
entity |
| Predicate | hasAthleticUse |
P5085
|
FINISHED |
| Object | university sports |
—
|
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: university sports | Statement: [West Campus (Queen's University), hasAthleticUse, university sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAthleticUse Context triple: [West Campus (Queen's University), hasAthleticUse, university sports]
-
A.
hasAthletics
Indicates that an entity participates in, is associated with, or offers athletics-related activities or programs.
-
B.
usedInSport
Indicates that something (such as an object, technique, or concept) is employed or utilized within the context of a particular sport.
-
C.
includesSport
Indicates that one entity contains, offers, or features a particular sport as part of its activities, content, or composition.
-
D.
appliesToSports
chosen
Indicates that something is relevant, appropriate, or specifically intended for use in the context of sports.
-
E.
hasAthlete
Indicates a relationship where an entity (such as a team, organization, or event) includes or is associated with one or more athletes.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab7d3984819089aefbf12d3b3c2c |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa781e1081909df006f730296c53 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.