Triple
T423186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schaefer Stadium |
E8148
|
entity |
| Predicate | sponsoredNamePeriod |
P13574
|
FINISHED |
| Object | Schaefer Stadium name used in the 1970s |
—
|
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: Schaefer Stadium name used in the 1970s | Statement: [Schaefer Stadium, sponsoredNamePeriod, Schaefer Stadium name used in the 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsoredNamePeriod Context triple: [Schaefer Stadium, sponsoredNamePeriod, Schaefer Stadium name used in the 1970s]
-
A.
sponsorshipDealStart
Indicates the point in time when a sponsorship agreement between parties officially begins.
-
B.
sponsorType
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
-
C.
sponsorInHouse
Indicates that one entity formally supports, promotes, or funds another entity within the same organization, institution, or internal setting.
-
D.
isOneOfLongestRunningNameplates
Indicates that the subject belongs to the group of products or models that have been produced or offered continuously for one of the longest time spans in their category.
-
E.
locationPeriod
Indicates that an entity is associated with being at a particular location during a specified time period.
- 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_69a2e7f1d1bc81909cf2dc9754a3c334 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eec200648190bcb9f1b98c8e9cdf |
completed | Feb. 28, 2026, 1:33 p.m. |
| PD | Predicate disambiguation | batch_69a2edd5439c8190aea661b8b4aa51e9 |
completed | Feb. 28, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69a2ee8b56d08190bd625626353d01b4 |
completed | Feb. 28, 2026, 1:32 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.