Triple
T4931644
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Purus River |
E110709
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Amazonas (Brazilian state) |
E367132
|
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: Amazonas (Brazilian state) | Statement: [Purus River, flowsThrough, Amazonas (Brazilian state)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amazonas (Brazilian state) Context triple: [Purus River, flowsThrough, Amazonas (Brazilian state)]
-
A.
Amazonas state
Amazonas state is Brazil’s largest and mostly rainforest-covered state in the northwest of the country, known for encompassing much of the Amazon River basin and the city of Manaus.
-
B.
Pará
Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
-
C.
Amapá
Amapá is a sparsely populated state in northern Brazil, located in the Amazon region along the Atlantic coast and bordering French Guiana.
-
D.
Amazonas
chosen
Amazonas is a vast state in northwestern Brazil, largely covered by the Amazon rainforest and known for its immense biodiversity and the city of Manaus.
-
E.
Várzea Paulista
Várzea Paulista is a municipality in southeastern Brazil known for its integration into the industrial and services corridor of the São Paulo metropolitan region.
- 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_69bd4415190c8190817bee7ec9f9f944 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd7063c57c8190a5a6fb3586238d35 |
completed | March 20, 2026, 4:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81c5f8ec8190834c624bae17adff |
completed | March 21, 2026, 11:32 a.m. |
Created at: March 20, 2026, 1:30 p.m.