Triple
T7259751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guayaramerín |
E159617
|
entity |
| Predicate | hasTransportConnectionWith |
P11026
|
FINISHED |
| Object | Guajará-Mirim |
E485405
|
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: Guajará-Mirim | Statement: [Guayaramerín, hasTransportConnectionWith, Guajará-Mirim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guajará-Mirim Context triple: [Guayaramerín, hasTransportConnectionWith, Guajará-Mirim]
-
A.
Guajará-Mirim
chosen
Guajará-Mirim is a Brazilian city in the state of Rondônia, located on the border with Bolivia in the western Amazon region.
-
B.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
C.
Morada Nova
Morada Nova is a municipality in the state of Ceará in northeastern Brazil, known for its agricultural activities and semi-arid landscape.
-
D.
Brejo Grande
Brejo Grande is a small coastal municipality in the Brazilian state of Sergipe, known for its location at the mouth of the São Francisco River.
-
E.
Itanhaém
Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eac5311c819094fc6880f3152813 |
completed | March 27, 2026, 8:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db175b188190beb5ba5ebb662c9b |
completed | March 28, 2026, 1:43 p.m. |
Created at: March 27, 2026, 2:57 p.m.