Triple
T23287965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seridó River |
E589943
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Caicó |
—
|
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: Caicó | Statement: [Seridó River, passesThrough, Caicó]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caicó Context triple: [Seridó River, passesThrough, Caicó]
-
A.
Caicó
chosen
Caicó is a municipality in the interior of Rio Grande do Norte, Brazil, known for its strong cultural traditions, especially its famous religious festivals and regional cuisine.
-
B.
Caraúbas
Caraúbas is a municipality in the state of Rio Grande do Norte in Brazil’s Northeast region.
-
C.
Braz de Aviz
Braz de Aviz is a Brazilian cardinal of the Roman Catholic Church known for his leadership roles in the Vatican, including as prefect of the Dicastery for Institutes of Consecrated Life and Societies of Apostolic Life.
-
D.
Aquidabã
Aquidabã is a municipality in the Brazilian state of Sergipe, located in the semi-arid interior region known as the sertão.
-
E.
Mauá
Mauá is an industrial and residential city located in the metropolitan region of São Paulo, Brazil.
- 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_69e25d1af9d88190a0b9b5e8fa608618 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19648842c81909756be4bc06b3a45 |
completed | April 29, 2026, 5:25 a.m. |
Created at: April 17, 2026, 5 p.m.