Triple
T34238121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Crisp |
E878387
|
entity |
| Predicate | mascotCatchphrase |
P91580
|
FINISHED |
| Object | Can’t get enough of that Golden Crisp |
—
|
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: Can’t get enough of that Golden Crisp | Statement: [Golden Crisp, mascotCatchphrase, Can’t get enough of that Golden Crisp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mascotCatchphrase Context triple: [Golden Crisp, mascotCatchphrase, Can’t get enough of that Golden Crisp]
-
A.
mascotSlogan
chosen
Indicates that a particular slogan is associated with or used by a specific mascot.
-
B.
mascotName
Indicates the name assigned to a mascot that represents an entity.
-
C.
mascotCharacteristic
Indicates that a mascot possesses or is associated with a particular characteristic or trait.
-
D.
mascotTheme
Indicates that an entity serves as the representative mascot associated with a particular theme, concept, or style.
-
E.
mascotCollectiveName
Indicates that a mascot is associated with and represents a particular collective group, organization, or team name.
- 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_69f349b22d8c819096b22df268382aa9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:56 a.m.