Triple
T28024833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fueled Up |
E707790
|
entity |
| Predicate | hasFictionalSportElement |
P32098
|
FINISHED |
| Object | surfing |
—
|
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: surfing | Statement: [Fueled Up, hasFictionalSportElement, surfing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalSportElement Context triple: [Fueled Up, hasFictionalSportElement, surfing]
-
A.
hasFantasyElement
Indicates that something includes or involves elements characteristic of fantasy, such as magic, mythical creatures, or imaginary worlds.
-
B.
featuresFictionalSport
chosen
Indicates that a work includes or showcases a fictional sport as part of its content or setting.
-
C.
hasAssociatedSportFigure
Indicates that an entity is linked or related to a particular sports figure (such as an athlete, coach, or sports personality).
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
hasFictionalEventType
Indicates that something is associated with, characterized by, or classified under a particular type or category of fictional event.
- 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_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fce7671f108190bf3ebf54339068b5 |
completed | May 7, 2026, 7:26 p.m. |
| PD | Predicate disambiguation | batch_69fce5b5a84c81908ac1b5b9f08d48d0 |
completed | May 7, 2026, 7:19 p.m. |
Created at: April 27, 2026, 8:12 p.m.