Triple
T9444121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parish of Vila do Bispo e Raposeira |
E227719
|
entity |
| Predicate | containsLocality |
P45140
|
FINISHED |
| Object | Raposeira |
E528985
|
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: Raposeira | Statement: [Parish of Vila do Bispo e Raposeira, containsLocality, Raposeira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raposeira Context triple: [Parish of Vila do Bispo e Raposeira, containsLocality, Raposeira]
-
A.
Raposeira
chosen
Raposeira is a small village in Portugal’s Algarve region, known for its rural charm and proximity to the Atlantic coast near Vila do Bispo.
-
B.
Carrasqueira
Carrasqueira is a steep, exposed rock-scramble section on the Pedra da Gávea hiking route in Rio de Janeiro, popular with adventurous climbers and hikers.
-
C.
Coruripe
Coruripe is a coastal municipality in northeastern Brazil known for its beaches, fishing activities, and sugarcane agriculture.
-
D.
Bérrio
Bérrio was a Portuguese carrack that served as one of the ships in Vasco da Gama’s pioneering fleet on the first voyage from Portugal to India.
-
E.
Tamarineira
Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f32aee88190a43573f97fa1e49d |
completed | April 1, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12cd9ae548190bf985c72196eb0bd |
completed | April 4, 2026, 3:23 p.m. |
Created at: March 30, 2026, 7:51 p.m.