Triple
T23458872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plessis-Robinson |
E568009
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Lapa, Brazil |
—
|
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: Lapa, Brazil | Statement: [Plessis-Robinson, hasTwinTown, Lapa, Brazil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lapa, Brazil Context triple: [Plessis-Robinson, hasTwinTown, Lapa, Brazil]
-
A.
Nova Lima, Brazil
Nova Lima is a city in the state of Minas Gerais, Brazil, known for its mining heritage, affluent residential areas, and proximity to the state capital Belo Horizonte.
-
B.
Bangú (Brazil)
Bangú is a Brazilian football club, traditionally known as Bangu Atlético Clube, based in the Bangu neighborhood of Rio de Janeiro.
-
C.
Lapa, Rio de Janeiro
chosen
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.
Itajubá, Brazil
Itajubá, Brazil is a city in the state of Minas Gerais known for its industrial base, particularly in aerospace and defense manufacturing, and for hosting a major Airbus Helicopters production facility.
-
E.
Upanema
Upanema is a municipality in the state of Rio Grande do Norte in Brazil’s Northeast region.
- 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_69e2458b4c888190b1d7998f9862a558 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a699c0088190a84d7a495a3e3d61 |
completed | April 29, 2026, 6:35 a.m. |
Created at: April 17, 2026, 5:53 p.m.