Triple
T15369995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pillsbury Company |
E367519
|
entity |
| Predicate | brandCharacterType |
P60013
|
FINISHED |
| Object | anthropomorphic dough figure |
—
|
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: anthropomorphic dough figure | Statement: [Pillsbury Company, brandCharacterType, anthropomorphic dough figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandCharacterType Context triple: [Pillsbury Company, brandCharacterType, anthropomorphic dough figure]
-
A.
brandCharacter
Indicates that one entity serves as a brand character or mascot representing another entity (typically a brand or product).
-
B.
characterTheme
Indicates that a particular theme, motif, or conceptual focus is associated with a given character.
-
C.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
-
D.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
-
E.
typeOfCharacter
chosen
Indicates that one entity is a specific kind or category of character in relation to another entity.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4b88a881909f9575c02aed287d |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca9ab7e88190a9261ef27be665b1 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:18 a.m.