Triple
T11101389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisville Bats |
E262512
|
entity |
| Predicate | usesSluggerBrandAssociation |
P97287
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Louisville Bats, usesSluggerBrandAssociation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSluggerBrandAssociation Context triple: [Louisville Bats, usesSluggerBrandAssociation, yes]
-
A.
associatedWithCityBranding
Indicates a relationship where something is connected to, involved in, or contributes to the branding or promotional identity of a city.
-
B.
associatedBrandCategory
Indicates that a brand is linked to or classified under a particular product or service category.
-
C.
referencesBrand
Indicates that one entity mentions, cites, or otherwise refers to a specific brand in its content or context.
-
D.
usesBrandCharacter
Indicates that one entity employs or features another entity’s brand character (such as a mascot or branded persona) in its materials, products, or communications.
-
E.
usedBrand
Indicates that an entity has utilized, applied, or operated a particular brand in some context.
- 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_69d6aa9a40d88190a373e2c7e48285db |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79a2ab09081908ffce2df8912b657 |
completed | April 9, 2026, 12:23 p.m. |
| PD | Predicate disambiguation | batch_69d7441aa3548190b92dbde57841c135 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750ca52ec8190a559432a5de106fd |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:27 p.m.