Triple
T1879700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ipanema Beach |
E39823
|
entity |
| Predicate | hasZone |
P6793
|
FINISHED |
| Object | Posto 9 |
E213057
|
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: Posto 9 | Statement: [Ipanema Beach, hasZone, Posto 9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Posto 9 Context triple: [Ipanema Beach, hasZone, Posto 9]
-
A.
Posto 9
chosen
Posto 9 is a famous and trendy stretch of Ipanema Beach in Rio de Janeiro, known for its lively social scene and iconic views.
-
B.
Posto 8
Posto 8 is a popular lifeguard-station beach area in Ipanema, Rio de Janeiro, known for its lively atmosphere and diverse crowds.
-
C.
Ponto de Parada
Ponto de Parada is a neighborhood in the city of Recife, Brazil, known primarily as a residential area within the metropolitan region.
-
D.
Linha do Tiro
Linha do Tiro is a neighborhood located in the city of Recife, in Brazil’s northeastern state of Pernambuco.
-
E.
Ossuccio
Ossuccio is a small lakeside locality on the western shore of Lake Como in northern Italy, known for its scenic setting opposite the historic Isola Comacina.
- 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_69a88633e4fc8190b7eb40463e048ec5 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0fa3d388190993073ffb0f60a84 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfba6e94c8190ad1daafbe7f70a44 |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:34 p.m.