Triple
T22143913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | São Francisco Valley |
E547235
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Juazeiro |
—
|
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: Juazeiro | Statement: [São Francisco Valley, majorCity, Juazeiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Juazeiro Context triple: [São Francisco Valley, majorCity, Juazeiro]
-
A.
Juazeiro
chosen
Juazeiro is a city in the state of Bahia, Brazil, located on the São Francisco River and known for its agricultural production and close integration with the neighboring city of Petrolina.
-
B.
Tamarineira
Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
-
C.
Guaiúba
Guaiúba is a municipality in the state of Ceará, Brazil, located in the metropolitan region of Fortaleza.
-
D.
Cajueiro
Cajueiro is a neighborhood within the city of Recife in northeastern Brazil.
-
E.
Mimoso do Sul
Mimoso do Sul is a municipality in southeastern Brazil known for its rural landscapes and agricultural-based local economy.
- 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_69e11e3a95d88190a3bd80d9471976c3 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129c045448190b3d189cdb8c0d2fd |
completed | April 28, 2026, 9:42 p.m. |
Created at: April 16, 2026, 8:32 p.m.