Triple
T26752735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wonder Pets Big Circus Bounce |
E674585
|
entity |
| Predicate | hasExperienceStyle |
P34300
|
FINISHED |
| Object | light thrill |
—
|
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: light thrill | Statement: [Wonder Pets Big Circus Bounce, hasExperienceStyle, light thrill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExperienceStyle Context triple: [Wonder Pets Big Circus Bounce, hasExperienceStyle, light thrill]
-
A.
experienceStyle
chosen
Indicates that one entity has or is associated with a particular manner, approach, or style in which an experience is delivered or undergone.
-
B.
hasExperienceElement
Indicates that an experience is composed of, or includes, a specific constituent element or component.
-
C.
hasExperienceOf
Indicates that one entity has undergone, encountered, or lived through a particular event, situation, or activity associated with another entity.
-
D.
hasPastExperience
Indicates that an entity has previously engaged in or undergone the specified activity, role, or situation in the past.
-
E.
hasNotableExperience
Indicates that an entity has a significant or distinguished experience related to another entity or context.
- 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_69eecda6e9dc81908452fab3ba17ed9b |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 27, 2026, 3:54 a.m.