Triple
T7437766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amapá |
E171661
|
entity |
| Predicate | hasBorderCheckpoint |
P10963
|
FINISHED |
| Object | Oiapoque |
E685284
|
NE 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: Oiapoque | Statement: [Amapá, hasBorderCheckpoint, Oiapoque]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oiapoque Context triple: [Amapá, hasBorderCheckpoint, Oiapoque]
-
A.
Oiapoque River
chosen
The Oiapoque River is a major river in northern South America that forms part of the border between Brazil and French Guiana before flowing into the Atlantic Ocean.
-
B.
Guajá
Guajá is an indigenous language of the Tupi–Guaraní family spoken by the Guajá people of the Brazilian Amazon.
-
C.
Ananindeua
Ananindeua is a major urban and industrial city in northern Brazil, located in the state of Pará within the Amazon region.
-
D.
Marabá
Marabá is a major industrial and commercial city in southeastern Pará, Brazil, known for its role in mining, steel production, and as a regional transportation hub.
-
E.
Barra de Mamanguape
Barra de Mamanguape is a coastal area in the state of Paraíba, Brazil, known for its estuary, mangrove ecosystems, and protected marine environments that include manatee habitats.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8d68a7e908190831b9f7f84ef19bd |
completed | March 29, 2026, 7:36 a.m. |
Created at: March 27, 2026, 3:13 p.m.