Triple
T15827293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Estádio Olímpico João Havelange |
E383775
|
entity |
| Predicate | locatedInNeighborhood |
P40
|
FINISHED |
| Object | Engenho de Dentro |
E826837
|
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: Engenho de Dentro | Statement: [Estádio Olímpico João Havelange, locatedInNeighborhood, Engenho de Dentro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Engenho de Dentro Context triple: [Estádio Olímpico João Havelange, locatedInNeighborhood, Engenho de Dentro]
-
A.
Engenho de Dentro
chosen
Engenho de Dentro is a neighborhood in Rio de Janeiro, Brazil, known for hosting the Estádio Nilton Santos football stadium.
-
B.
Engenho do Meio
Engenho do Meio is a neighborhood located in the city of Recife, in the state of Pernambuco, Brazil.
-
C.
Vale dos Sinos
Vale dos Sinos is a populous and industrialized region in the state of Rio Grande do Sul, Brazil, known especially for its footwear and leather industries.
-
D.
Aleijadinho
Aleijadinho was an influential 18th-century Brazilian sculptor and architect, renowned for his baroque and rococo religious works in colonial Brazil.
-
E.
Cidade Nova
Cidade Nova is a central neighborhood in Rio de Janeiro, Brazil, known for its mix of residential areas, government offices, and important transport links.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e11e60fe748190baa49c49605efd0d |
completed | April 16, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff999da5008190921b3f129787999e |
completed | May 9, 2026, 8:31 p.m. |
Created at: April 10, 2026, 4:49 a.m.