Triple
T15705301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mourão Municipality |
E380692
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Mourão |
E384237
|
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: Mourão | Statement: [Mourão Municipality, seat, Mourão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mourão Context triple: [Mourão Municipality, seat, Mourão]
-
A.
Mourão
chosen
Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
-
B.
Guaratinguetá
Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
-
C.
Garça
Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
-
D.
Duas Barras
Duas Barras is a small municipality in the mountainous interior of Rio de Janeiro state in southeastern Brazil.
-
E.
Sertãozinho
Sertãozinho is a municipality in the interior of Brazil known for its strong sugarcane-based agribusiness and ethanol production.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f6fc3608190a85b25755f5345db |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff997fe6f48190813bde2bfc11c253 |
completed | May 9, 2026, 8:30 p.m. |
Created at: April 10, 2026, 4:45 a.m.