Triple
T23480690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lloyd Bridges as Steve McCroskey |
E570395
|
entity |
| Predicate | basedOnGenreParodyOf |
P43127
|
FINISHED |
| Object | 1970s disaster movies |
—
|
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: 1970s disaster movies | Statement: [Lloyd Bridges as Steve McCroskey, basedOnGenreParodyOf, 1970s disaster movies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnGenreParodyOf Context triple: [Lloyd Bridges as Steve McCroskey, basedOnGenreParodyOf, 1970s disaster movies]
-
A.
parodies
Indicates that one entity imitates another in an exaggerated or humorous way, often to criticize or comment on the original.
-
B.
isComedySongBy
Indicates that a song belongs to the comedy genre and is performed or created by a specified artist or group.
-
C.
hasHumorousTreatmentOf
chosen
Indicates that one entity presents or portrays another entity in a humorous, comedic, or joking manner.
-
D.
originalHitPerformerParodied
Indicates that the subject is the original performer of a hit work that is being parodied by the object.
-
E.
adaptedWorkOf
Indicates that one work is derived from, based on, or reinterprets the content of another pre-existing work.
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a75002008190b02fbffd94e5e8b1 |
completed | April 29, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f0620ac3608190b36916261ea50f54 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:03 p.m.