Triple
T55415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reser Stadium |
E1094
|
entity |
| Predicate | hasLockerRooms |
P105
|
FINISHED |
| Object | home and visitor locker rooms |
—
|
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: home and visitor locker rooms | Statement: [Reser Stadium, hasLockerRooms, home and visitor locker rooms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLockerRooms Context triple: [Reser Stadium, hasLockerRooms, home and visitor locker rooms]
-
A.
hasRestrooms
Indicates that a place or facility provides access to restroom or toilet amenities.
-
B.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
-
C.
hasNotableFacility
chosen
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
-
D.
numberOfChambers
Indicates the count of distinct chambers or compartments associated with an entity.
-
E.
hasElevators
Indicates that one entity is equipped with or contains one or more elevators for vertical transportation.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b3a9e848190b80de3c858678b3a |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ac52fb08190aa7c38f83434f795 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.