Triple
T19432305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tancredo Neves International Airport |
E486145
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Confins |
—
|
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: Confins | Statement: [Tancredo Neves International Airport, locatedIn, Confins]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Confins Context triple: [Tancredo Neves International Airport, locatedIn, Confins]
-
A.
Confins
chosen
Confins is a municipality in the Brazilian state of Minas Gerais, best known for hosting the Belo Horizonte-Confins International Airport that serves the Belo Horizonte metropolitan area.
-
B.
Montes Claros
Montes Claros is a town and municipality in northeastern Brazil’s state of Minas Gerais, known as a regional commercial and industrial center.
-
C.
Uberaba
Uberaba is a mid-sized Brazilian city in the western part of Minas Gerais state, known for its strong agribusiness sector and cattle breeding traditions.
-
D.
Betim
Betim is a riverside village and ferry point in North Goa, India, located across the Mandovi River from Panaji and known for its transport links and scenic waterfront.
-
E.
Betim
Betim is an industrial city in southeastern Brazil known for its major automotive and petrochemical complexes.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6335c2d7481909a44b45d95492e02 |
completed | April 20, 2026, 2:08 p.m. |
Created at: April 10, 2026, 1:37 p.m.