Triple
T5532011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edward R. Rooney |
E145069
|
entity |
| Predicate | comicElement |
P43839
|
FINISHED |
| Object | slapstick misfortunes |
—
|
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: slapstick misfortunes | Statement: [Edward R. Rooney, comicElement, slapstick misfortunes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comicElement Context triple: [Edward R. Rooney, comicElement, slapstick misfortunes]
-
A.
comicFunction
chosen
Indicates a relationship where something serves a humorous or entertainment role, such as providing comedy, comic relief, or a joking purpose within a context.
-
B.
comicPublisher
Indicates that one entity is the publisher responsible for producing or distributing the comic associated with another entity.
-
C.
hasComicSeries
Indicates that one entity is the comic series to which another entity belongs or with which it is associated.
-
D.
featuresCharactersFrom
Indicates that one entity (such as a work or production) includes or presents characters originating from another entity.
-
E.
hasFictionalIssue
Indicates that one entity possesses, is associated with, or is characterized by a particular fictional problem, flaw, or complication.
- 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_69c008f9955881909bfa8348b56b4739 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f9d17ec8190b93b12931a4c1b33 |
completed | March 22, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:34 p.m.