Triple
T27104751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Two Tars |
E686535
|
entity |
| Predicate | hasSlapstickElement |
P14479
|
FINISHED |
| Object | destruction of automobiles |
—
|
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: destruction of automobiles | Statement: [Two Tars, hasSlapstickElement, destruction of automobiles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSlapstickElement Context triple: [Two Tars, hasSlapstickElement, destruction of automobiles]
-
A.
hasComedyElements
Indicates that something contains humorous or comedic aspects as part of its overall content or style.
-
B.
hasHumorType
chosen
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
C.
hasStunts
Indicates that one entity performs, includes, or is associated with stunt actions for another entity or context.
-
D.
hasLaughTrack
Indicates that a piece of media includes an added or artificial laughter audio track accompanying its content.
-
E.
usesInComedy
Indicates that something is employed or incorporated as a humorous element within a comedic context or performance.
- 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_69ef148accd48190b6ed6e13a15f2a4f |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f623fcc6c881908e76b65c0ee51dd4 |
completed | May 2, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69f620e0b37481909a280574decbd443 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 8:50 a.m.