Triple
T25831633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Here Comes Cookie |
E650678
|
entity |
| Predicate | hasFictionalStyle |
P33843
|
FINISHED |
| Object | farce |
—
|
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: farce | Statement: [Here Comes Cookie, hasFictionalStyle, farce]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalStyle Context triple: [Here Comes Cookie, hasFictionalStyle, farce]
-
A.
hasFictionalCitationStyle
Indicates that one entity uses or is associated with a citation or referencing style that is fictional or not used in real-world practice.
-
B.
hasFictionalForm
chosen
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
C.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
D.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
-
E.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
- 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6e6029a10819098ff21f58079e70e |
completed | May 3, 2026, 6:06 a.m. |
| PD | Predicate disambiguation | batch_69f6e3d5e8188190b1e1c2e5d1b77031 |
completed | May 3, 2026, 5:57 a.m. |
Created at: April 22, 2026, 7:38 a.m.