Triple
T32295371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kilgore Trout |
E825077
|
entity |
| Predicate | hasFictionalBibliography |
P56229
|
FINISHED |
| Object | numerous imaginary novels and stories |
—
|
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: numerous imaginary novels and stories | Statement: [Kilgore Trout, hasFictionalBibliography, numerous imaginary novels and stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalBibliography Context triple: [Kilgore Trout, hasFictionalBibliography, numerous imaginary novels and stories]
-
A.
hasFictionalWork
chosen
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
B.
hasFictionalDocument
Indicates that one entity possesses, is associated with, or includes a document that is fictional or exists only within an imagined or narrative context.
-
C.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
-
D.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
E.
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.
- 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_69f349101b788190b4f14884dc7d1ed2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fec4cffed08190b5e5e7cc0c87493e |
completed | May 9, 2026, 5:23 a.m. |
| PD | Predicate disambiguation | batch_69fec2ea7fe08190bd751b39515f69d1 |
completed | May 9, 2026, 5:15 a.m. |
Created at: May 1, 2026, 12:44 a.m.