Triple
T26697922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Basketball Academy |
E673074
|
entity |
| Predicate | nonProfessionalLevel |
P143376
|
FINISHED |
| Object | amateur |
—
|
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: amateur | Statement: [Giant Basketball Academy, nonProfessionalLevel, amateur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nonProfessionalLevel Context triple: [Giant Basketball Academy, nonProfessionalLevel, amateur]
-
A.
nonProfessional
chosen
Indicates that the relationship or activity is carried out in an informal or amateur capacity rather than as part of a recognized profession or paid occupation.
-
B.
nonScholastic
Indicates that an activity, event, or attribute is related to areas outside formal academic or scholarly pursuits.
-
C.
professionalBase
Indicates that one entity serves as the primary professional location, organization, or base of operations for another entity.
-
D.
traditionalLevel
Indicates the degree to which something adheres to established customs, practices, or traditions.
-
E.
professional
Indicates that one entity has a formal, occupation-related role, service, or expertise in relation to another entity.
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f61a17a7788190946f7e32d63cd43f |
completed | May 2, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
Created at: April 27, 2026, 3:29 a.m.