Triple
T21652408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazilian semi-arid region |
E534369
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Aracati |
—
|
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: Aracati | Statement: [Brazilian semi-arid region, hasCity, Aracati]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aracati Context triple: [Brazilian semi-arid region, hasCity, Aracati]
-
A.
Aracati
chosen
Aracati is a historic coastal city in northeastern Brazil known for its colonial architecture and nearby Canoa Quebrada beach.
-
B.
Araricá
Araricá is a small municipality in the state of Rio Grande do Sul, Brazil, known for its rural character and integration into the Porto Alegre metropolitan region.
-
C.
Arapiraca
Arapiraca is a major city in the Brazilian state of Alagoas, known as an important regional commercial and agricultural center.
-
D.
Quixeramobim
Quixeramobim is a municipality in northeastern Brazil known for its semi-arid landscape and agricultural activities within the state of Ceará.
-
E.
Itabaiana
Itabaiana is a prominent inland city in the Brazilian state of Sergipe, known for its vibrant commerce, agricultural production, and strategic location as a regional hub.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 16, 2026, 6:36 p.m.