Triple
T16361189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mesão Frio |
E397312
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Baião |
E740608
|
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: Baião | Statement: [Mesão Frio, borderedBy, Baião]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baião Context triple: [Mesão Frio, borderedBy, Baião]
-
A.
Baião
chosen
Baião is a Portuguese wine subregion within Vinho Verde, known for producing fresh, aromatic white wines, often from the Avesso grape.
-
B.
Carriço
Carriço is a civil parish within the municipality of Pombal in central Portugal, known for its rural character and local community life.
-
C.
Santana de Parnaíba
Santana de Parnaíba is a historic municipality in the São Paulo metropolitan region of Brazil, known for its well-preserved colonial architecture and cultural heritage.
-
D.
Macuco
Macuco is a small municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
-
E.
Arapiraca
Arapiraca is a major city in the Brazilian state of Alagoas, known as an important regional commercial and agricultural center.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad304448190b3f6f0350a1e151d |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dbeabe081909e3d02676293e8b2 |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:08 a.m.