Triple
T19566840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mato Grosso |
E489604
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Goiás |
—
|
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: Goiás | Statement: [Mato Grosso, borderedBy, Goiás]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goiás Context triple: [Mato Grosso, borderedBy, Goiás]
-
A.
Goiás
chosen
Goiás is a large inland state in central Brazil known for its agricultural production, Cerrado savanna landscapes, and the regional capital city of Goiânia.
-
B.
Mato Grosso do Sul
Mato Grosso do Sul is a landlocked state in Brazil’s Center-West region, known for its vast Pantanal wetlands, rich biodiversity, and cattle ranching economy.
-
C.
Minas Gerais
Minas Gerais is a large, historically rich state in southeastern Brazil known for its colonial-era towns, mining heritage, and significant cultural and architectural landmarks.
-
D.
Paraná state
Paraná state is a southern Brazilian state known for its diverse landscapes, major agricultural production, and popular natural attractions including part of the Iguaçu National Park.
-
E.
Aragua state
Aragua state is a central Venezuelan state known for its capital city Maracay, industrial activity, and diverse landscapes that include coastal areas and national parks.
- 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63f784ff88190a515c78429de3caf |
completed | April 20, 2026, 3 p.m. |
Created at: April 10, 2026, 1:42 p.m.