Triple
T14495649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doce River |
E359489
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object | Linhares |
E952783
|
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: Linhares | Statement: [Doce River, flowsNear, Linhares]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linhares Context triple: [Doce River, flowsNear, Linhares]
-
A.
Linhares
chosen
Linhares is a municipality in southeastern Brazil known for its extensive lake system, agricultural production, and coastal location within the state of Espírito Santo.
-
B.
Morrinhos
Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
-
C.
Domingos Martins
Domingos Martins is a municipality in the Brazilian state of Espírito Santo known for its strong German cultural heritage, reflected in its architecture, festivals, and local traditions.
-
D.
Vila Velha
Vila Velha is a major coastal city in southeastern Brazil known for its beaches, historic sites, and role as a key urban and economic center in the state of Espírito Santo.
-
E.
Santo Amaro
Santo Amaro is a central neighborhood in Recife, Brazil, known for its mix of residential areas, commerce, and important urban infrastructure.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de93109cb081909a6e846db23a4635 |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9731588190b27a826582e5fc6d |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 10, 2026, 1:21 a.m.