Triple
T18447923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ribeira Grande |
E450704
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Ponta do Sol |
—
|
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: Ponta do Sol | Statement: [Ribeira Grande, hasNearbySettlement, Ponta do Sol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ponta do Sol Context triple: [Ribeira Grande, hasNearbySettlement, Ponta do Sol]
-
A.
Ponta do Sol
chosen
Ponta do Sol is a coastal town on the island of Santo Antão in Cape Verde, known for its dramatic oceanfront setting and role as a local administrative and fishing center.
-
B.
Armação dos Búzios
Armação dos Búzios is a popular Brazilian coastal resort town in the state of Rio de Janeiro, renowned for its beaches, nightlife, and upscale tourism.
-
C.
Rio das Ostras
Rio das Ostras is a coastal municipality in the state of Rio de Janeiro, Brazil, known for its beaches, tourism, and growing urban development.
-
D.
Búzios
Búzios is a popular Brazilian coastal resort town on the Atlantic Ocean, known for its beaches, nightlife, and upscale tourism.
-
E.
Cabo Frio
Cabo Frio is a coastal city in southeastern Brazil known for its white-sand beaches, clear waters, and tourism-driven 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e52645cb88819086b0e70b6613edcd |
completed | April 19, 2026, 7 p.m. |
Created at: April 10, 2026, 11:30 a.m.