Triple
T1141727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIBA |
E23465
|
entity |
| Predicate | numberOfNationalFederations |
P24376
|
FINISHED |
| Object | over 200 |
—
|
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: over 200 | Statement: [FIBA, numberOfNationalFederations, over 200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNationalFederations Context triple: [FIBA, numberOfNationalFederations, over 200]
-
A.
numberOfLeagues
Indicates the quantity of leagues associated with or attributed to a given entity or relationship.
-
B.
numberOfNationalSocieties
Indicates the total count of national societies associated with or recognized by a given entity.
-
C.
associatedConfederationCount
Indicates the number of distinct confederations with which an entity is associated.
-
D.
confederationsRepresented
Indicates that one entity serves as an official representative or member of one or more confederations within a given context.
-
E.
numberOfTeamsInUnitedStates
Indicates the total count of teams that are located within or belong to the United States.
- 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_69a493ef399c8190b04b9146d2314f59 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc4d414881908fc636e8ccbc4c34 |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4d4104819084027a043c6118cb |
completed | March 1, 2026, 10:18 p.m. |
| PDg | Predicate description generation | batch_69a4bbb9fb4c81909dd39c496893c21b |
completed | March 1, 2026, 10:20 p.m. |
Created at: March 1, 2026, 7:44 p.m.