Triple
T4726622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Norman Brinker |
E104899
|
entity |
| Predicate | genreOfBusinessInnovation |
P16245
|
FINISHED |
| Object | casual dining restaurant format |
—
|
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: casual dining restaurant format | Statement: [Norman Brinker, genreOfBusinessInnovation, casual dining restaurant format]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfBusinessInnovation Context triple: [Norman Brinker, genreOfBusinessInnovation, casual dining restaurant format]
-
A.
innovationArea
chosen
Indicates the thematic or domain-specific field in which an innovation is focused or applied.
-
B.
innovationFrom
Indicates that something originates, arises, or is derived as an innovation from a particular source or prior entity.
-
C.
hasGenreInnovation
Indicates that something introduces a novel or pioneering approach within its genre or category.
-
D.
entrepreneurialDomain
Indicates that an entity operates within, is associated with, or belongs to a particular field or sector of entrepreneurial activity.
-
E.
innovation
Indicates the introduction or development of something new or significantly improved compared to existing methods, products, or ideas.
- 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_69bd43ed84648190ae0b7ee8e8d00482 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:18 p.m.