Triple
T23129399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodovia Rio-Santos |
E577125
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | São Sebastião |
—
|
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: São Sebastião | Statement: [Rodovia Rio-Santos, passesNear, São Sebastião]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: São Sebastião Context triple: [Rodovia Rio-Santos, passesNear, São Sebastião]
-
A.
São Sebastião
São Sebastião is a civil parish in the municipality of Ponta Delgada on São Miguel Island in Portugal’s Azores archipelago.
-
B.
São Sebastião
chosen
São Sebastião is a coastal municipality in the state of São Paulo, Brazil, known for its beaches, tourism, and role as a port city.
-
C.
São Sebastião
São Sebastião is a civil parish within the municipality of Rio Maior in Portugal, known for its local community and role in the region’s administrative organization.
-
D.
São Sebastião do Rio de Janeiro
São Sebastião do Rio de Janeiro is the formal, historical name of the Brazilian city of Rio de Janeiro, originally dedicated to Saint Sebastian.
-
E.
Nazaré Paulista
Nazaré Paulista is a municipality in the state of São Paulo, Brazil, known for its natural landscapes and reservoirs that supply water to the metropolitan region.
- 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_69e245f7b0e481909c473ff4e6a54e2c |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18e8671f48190887e57d5723e49c1 |
completed | April 29, 2026, 4:52 a.m. |
Created at: April 17, 2026, 4 p.m.