Triple
T23212040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosario |
E580621
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Rosário |
—
|
NE NERFINISHED |
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: Rosário | Statement: [Rosario, hasVariant, Rosário]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosário Context triple: [Rosario, hasVariant, Rosário]
-
A.
Rosário
chosen
Rosário is a municipality in the Brazilian state of Maranhão, known for its regional culture and role in the state's interior.
-
B.
Canoas
Canoas is a major industrial and residential city in the Porto Alegre metropolitan region of Rio Grande do Sul, Brazil.
-
C.
Sampa
Sampa is a celebrated Brazilian song by Caetano Veloso that poetically reflects on the city of São Paulo and its cultural atmosphere.
-
D.
Rosario
Rosario is a first-class agricultural municipality in the province of Batangas in the Philippines, known for its coconut and rice farming.
-
E.
Rosario
Rosario is a coastal municipality in the province of Cavite in the Philippines, known for its fishing industry and proximity to Manila Bay.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2460389408190be74f41d217799a9 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f191620378819096362252c3b819b6 |
completed | April 29, 2026, 5:04 a.m. |
Created at: April 17, 2026, 4:07 p.m.