Triple
T11734682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michigan Wolverines |
E278993
|
entity |
| Predicate | helmetDesignFeature |
P101062
|
FINISHED |
| Object | winged helmet (football) |
—
|
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: winged helmet (football) | Statement: [Michigan Wolverines, helmetDesignFeature, winged helmet (football)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: helmetDesignFeature Context triple: [Michigan Wolverines, helmetDesignFeature, winged helmet (football)]
-
A.
helmetType
Indicates the specific category or style of helmet associated with an entity.
-
B.
helmetLogo
Indicates that one entity serves as the logo or emblem displayed on the helmet of another entity.
-
C.
helmetColor
Indicates the specific color attribute assigned to a helmet in the relationship.
-
D.
helmetPolicy
Indicates that there is a rule or requirement governing whether and how helmets must be worn in a given context.
-
E.
helmetNumber
Indicates the identifying number assigned to a person or object as displayed on their helmet.
- 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4edced48190b7a59dd45921828e |
completed | April 10, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:41 p.m.