Triple
T8834608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bakairi language |
E210234
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Mato Grosso |
E489604
|
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: Mato Grosso | Statement: [Bakairi language, region, Mato Grosso]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mato Grosso Context triple: [Bakairi language, region, Mato Grosso]
-
A.
Mato Grosso
chosen
Mato Grosso is a large inland state in west-central Brazil known for its vast Amazon rainforest, Pantanal wetlands, and agricultural frontier.
-
B.
Rondônia
Rondônia is a state in northern Brazil known for its Amazon rainforest areas, agricultural frontier, and diverse immigrant communities, including a significant population of German Brazilians.
-
C.
Tocantins
Tocantins is a central Brazilian state known for its relatively recent creation in 1988, its capital Palmas, and its mix of Amazonian and cerrado ecosystems.
-
D.
Pará
Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
-
E.
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.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60686cac8190b3138db40b6fe058 |
completed | April 1, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa069d7488190ade4caa15fa83cd9 |
completed | April 3, 2026, 11:11 a.m. |
Created at: March 30, 2026, 6:47 p.m.