Triple
T37813209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woody Woodpecker |
E942704
|
entity |
| Predicate | themeParkMascotFor |
P189241
|
FINISHED |
| Object | Universal Studios theme parks |
—
|
NE NERFINISHED |
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: Universal Studios theme parks | Statement: [Woody Woodpecker, themeParkMascotFor, Universal Studios theme parks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeParkMascotFor Context triple: [Woody Woodpecker, themeParkMascotFor, Universal Studios theme parks]
-
A.
mascotTheme
Indicates that an entity serves as the representative mascot associated with a particular theme, concept, or style.
-
B.
typeOfMascot
Indicates that one entity is a mascot and specifies the category or kind of mascot it is (e.g., animal, human, object, etc.).
-
C.
themeParkBranding
Indicates that a theme park is branded, themed, or marketed under a particular brand, franchise, or intellectual property.
-
D.
mascotCharacteristic
Indicates that a mascot possesses or is associated with a particular characteristic or trait.
-
E.
mascotDesigner
Indicates that one entity is responsible for designing or creating the mascot associated with another entity.
- F. None of above. chosen
Provenance (4 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_69f76ee8104c8190ab17133ccd8f86e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbb9e8108c8190ae1c7940b1677e95 |
completed | May 6, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fbb141605c8190b9c27d70352522db |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbb9e69b7481909beaf8264d87c5e5 |
completed | May 6, 2026, 10 p.m. |
Created at: May 3, 2026, 4:19 p.m.