Triple
T26666465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clube de Regatas Brasil |
E672198
|
entity |
| Predicate | hasStrongRegionalPresence |
P32293
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Clube de Regatas Brasil, hasStrongRegionalPresence, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrongRegionalPresence Context triple: [Clube de Regatas Brasil, hasStrongRegionalPresence, true]
-
A.
hasRegionStrongPresence
chosen
Indicates that an entity maintains a significant, influential, or concentrated presence within a specified region.
-
B.
hasRegionalEntity
Indicates that one entity includes, governs, or is associated with another entity that functions as its regional subdivision or component.
-
C.
hasRegionalSignificance
Indicates that something holds particular importance, influence, or relevance within a specific geographic region.
-
D.
hasRegionalServices
Indicates that an entity provides or is associated with services that operate within a specific geographic region or set of regions.
-
E.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
- 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_69eecda00a9c8190b2691f4d89db03b6 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f7675b12848190a3569cfda29c5b0e |
completed | May 3, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69f762f4b59481909f70074f11825bfb |
completed | May 3, 2026, 3 p.m. |
Created at: April 27, 2026, 3:10 a.m.