Triple
T1119444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose Bowl |
E11175
|
entity |
| Predicate | hasStadiumUse |
P25179
|
FINISHED |
| Object | college football games |
—
|
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: college football games | Statement: [Rose Bowl, hasStadiumUse, college football games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStadiumUse Context triple: [Rose Bowl, hasStadiumUse, college football games]
-
A.
containsStadium
Indicates that a location or area includes a stadium within its boundaries or premises.
-
B.
playedAtStadium
Indicates that an event or game took place at, or was hosted in, a specific stadium.
-
C.
usesStadiumAsOffice
Indicates that an entity utilizes a stadium facility as its primary place of business or administrative operations.
-
D.
homeStadiumUse
Indicates that a particular stadium is used as the home venue by a specific team or organization.
-
E.
locatedInStadium
Indicates that an entity is situated within or at the premises of a specific stadium.
- F. None of above. chosen
Provenance (4 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4562f48190831e959f5f309956 |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bc47fce48190825d3a877251f789 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:43 p.m.