Triple
T33087763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fazza |
E846687
|
entity |
| Predicate | sportsHobby |
P24884
|
FINISHED |
| Object | skydiving |
—
|
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: skydiving | Statement: [Fazza, sportsHobby, skydiving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsHobby Context triple: [Fazza, sportsHobby, skydiving]
-
A.
sportsAndRecreation
chosen
Indicates a relationship where an entity is associated with, involved in, or designated for sports or recreational activities.
-
B.
sportCreated
Indicates that an entity is the originator or inventor of a particular sport.
-
C.
sportsInvolvement
Indicates the nature or extent of an entity’s participation in, association with, or role within a sport or sporting activity.
-
D.
sportFounded
Indicates that an entity (such as a sports team, club, or organization) was established or created by another entity.
-
E.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
- 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_69f34954d46c8190a04a159cc5f99efd |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:26 a.m.