Triple
T6140241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forrest J Ackerman |
E136941
|
entity |
| Predicate | knownForStyle |
P46274
|
FINISHED |
| Object | humorous editorial voice |
—
|
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: humorous editorial voice | Statement: [Forrest J Ackerman, knownForStyle, humorous editorial voice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForStyle Context triple: [Forrest J Ackerman, knownForStyle, humorous editorial voice]
-
A.
notableWorkStyle
Indicates a stylistic characteristic or distinctive manner associated with a notable work created by the subject.
-
B.
notableStyleFeature
chosen
Indicates that an entity possesses a distinctive stylistic characteristic or design element that is especially noteworthy or defining.
-
C.
knownForCoverageStyle
Indicates that an entity is recognized or distinguished by a particular style or manner of coverage (e.g., how it reports on or presents information or events).
-
D.
knownForCollectionOf
Indicates that one entity is recognized or notable specifically for its collection or assemblage of another type of entity.
-
E.
styleSpecialty
Indicates a relationship where an entity’s expertise, focus, or specialization is in a particular style or stylistic approach.
- 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cb030fc8190b78e4967eea65611 |
completed | March 22, 2026, 9:18 p.m. |
| PD | Predicate disambiguation | batch_69c055f19b0c81908be34a00ab218723 |
completed | March 22, 2026, 8:49 p.m. |
Created at: March 22, 2026, 4:15 p.m.