Triple
T22644225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron of Rio Branco |
E558911
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object | Rio de Janeiro |
—
|
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: Rio de Janeiro | Statement: [Baron of Rio Branco, burialPlace, Rio de Janeiro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio de Janeiro Context triple: [Baron of Rio Branco, burialPlace, Rio de Janeiro]
-
A.
Rio de Janeiro
chosen
Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
-
B.
Río de Janeiro
Río de Janeiro is a station on Buenos Aires Underground Line A in Argentina’s capital city.
-
C.
Lapa, Rio de Janeiro
Lapa, Rio de Janeiro is a historic and bohemian neighborhood in central Rio known for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
-
D.
Niterói
Niterói is a coastal city in the state of Rio de Janeiro, Brazil, known for its beaches, views of Rio across the bay, and iconic modernist architecture by Oscar Niemeyer.
-
E.
Caju (Rio de Janeiro)
Caju is a neighborhood in Rio de Janeiro, Brazil, known for its large port area, cemeteries, and proximity to the city’s industrial and docklands zones.
- 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_69e24547f7fc819086e2c4ba3b979657 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f170366ac881909e9d1dd2e7cf7a25 |
completed | April 29, 2026, 2:43 a.m. |
Created at: April 17, 2026, 3:05 p.m.