Triple
T8796197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Posto 8 |
E209293
|
entity |
| Predicate | near |
P350
|
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: [Posto 8, near, Posto 9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Posto 9 Context triple: [Posto 8, near, 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 7
Posto 7 is one of the numbered beachfront lifeguard and gathering points along Rio de Janeiro’s famous beaches, commonly used as a reference spot by locals and visitors.
-
C.
Posto 8
Posto 8 is a popular lifeguard-station beach area in Ipanema, Rio de Janeiro, known for its lively atmosphere and diverse crowds.
-
D.
Posto 10
Posto 10 is a popular lifeguard station area and beach section in Ipanema, Rio de Janeiro, known for its vibrant social scene and scenic oceanfront.
-
E.
Posto
Posto is a Bengali-language family drama film that explores generational conflict and custody battles within a modern Indian family.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fa24ca08190a7738a7f1c446456 |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf890b49048190b49c784f84e23496 |
completed | April 3, 2026, 9:31 a.m. |
Created at: March 30, 2026, 6:44 p.m.