Triple
T6592581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIBA Europe |
E148397
|
entity |
| Predicate | numberOfMemberFederations |
P24376
|
FINISHED |
| Object | 50+ |
—
|
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: 50+ | Statement: [FIBA Europe, numberOfMemberFederations, 50+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMemberFederations Context triple: [FIBA Europe, numberOfMemberFederations, 50+]
-
A.
numberOfNationalFederations
chosen
Indicates the total count of national federations associated with or governed by a given entity.
-
B.
numberOfRegionalMembers
Indicates the quantity of members associated with or belonging to a specific region within a given context.
-
C.
numberOfMemberOrganizations
Indicates the total count of organizations that are members of a given group, association, or umbrella entity.
-
D.
numberOfMemberNOCs
Indicates the total count of National Olympic Committees (NOCs) that are members of a given organization or group.
-
E.
associatedConfederationCount
Indicates the number of distinct confederations with which an entity is associated.
- 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_69c687e7b8688190811ffee72e096468 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:55 p.m.