Triple
T28714888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michigan Go Blue banner run-through |
E729930
|
entity |
| Predicate | textOnBanner |
P165254
|
FINISHED |
| Object | Go Blue |
—
|
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: Go Blue | Statement: [Michigan Go Blue banner run-through, textOnBanner, Go Blue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textOnBanner Context triple: [Michigan Go Blue banner run-through, textOnBanner, Go Blue]
-
A.
bannerType
Indicates the specific category or style of a banner associated with an entity or context.
-
B.
presentedUnderBanner
Indicates that something is displayed or showcased beneath or associated with a specific banner or heading.
-
C.
textBy
Indicates that a given text or written content was authored or produced by a particular entity.
-
D.
bannerColor
Indicates the color associated with a banner in the relationship or context described.
-
E.
usedBanner
Indicates that one entity employed or displayed another entity as a banner in some context or setting.
- 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_69f043e7d5a4819094b18aca10b1e024 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65705a3048190a3728b695ba2ae65 |
completed | May 2, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 5:50 a.m.