Triple
T22288078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FIBA 3x3 rules |
E550915
|
entity |
| Predicate | officialsNumber |
P67611
|
FINISHED |
| Object | 1 or 2 referees on court depending on competition level |
—
|
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: 1 or 2 referees on court depending on competition level | Statement: [FIBA 3x3 rules, officialsNumber, 1 or 2 referees on court depending on competition level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialsNumber Context triple: [FIBA 3x3 rules, officialsNumber, 1 or 2 referees on court depending on competition level]
-
A.
numberOfOfficials
chosen
Indicates the total count of officials associated with a given entity or context.
-
B.
officeHoldersNumber
Indicates the number of individuals who hold a particular office or position.
-
C.
governmentNumber
Indicates that an entity is assigned a specific official identification number by a government authority.
-
D.
numberOfGovernment
Indicates the quantity of governmental bodies or administrations associated with an entity.
-
E.
correspondingGovernmentOffice
Indicates that one entity is the official government office responsible for handling matters related to the other 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_69e11e44d538819097c6b8f333af3352 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1560896348190985725ac8ad406b3 |
completed | April 29, 2026, 12:51 a.m. |
| PD | Predicate disambiguation | batch_69e72ffa438481908f80879aef2a589b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:40 p.m.