Triple
T12813274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2015 FIBA Americas Women's Championship |
E306323
|
entity |
| Predicate | numberOfFederations |
P24376
|
FINISHED |
| Object | 44 |
—
|
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: 44 | Statement: [2015 FIBA Americas Women's Championship, numberOfFederations, 44]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFederations Context triple: [2015 FIBA Americas Women's Championship, numberOfFederations, 44]
-
A.
numberOfNationalFederations
chosen
Indicates the total count of national federations associated with or governed by a given entity.
-
B.
associatedConfederationCount
Indicates the number of distinct confederations with which an entity is associated.
-
C.
federation
Indicates that an entity is formally associated with, governed by, or part of a larger federated organization or system.
-
D.
federalSubjectCount
Indicates the number of federal subjects (administrative units within a federation) associated with or contained by an entity.
-
E.
numberOfColonies
Indicates the count of distinct colonies associated with or possessed by a given 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9adcf08190a12801adcc613477 |
completed | April 10, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69d9640ed7448190b276e7fab649f7d2 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:31 p.m.