Triple
T6299248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pacatuba |
E141209
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Maracanaú |
E162410
|
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: Maracanaú | Statement: [Pacatuba, borderedBy, Maracanaú]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maracanaú Context triple: [Pacatuba, borderedBy, Maracanaú]
-
A.
Maracanaú
chosen
Maracanaú is an industrial and residential city in northeastern Brazil, located in the metropolitan region of Fortaleza in the state of Ceará.
-
B.
Vitória de Santo Antão
Vitória de Santo Antão is a municipality in northeastern Brazil known for its sugarcane-based economy, cachaça production, and colonial-era heritage.
-
C.
Cumbuco
Cumbuco is a coastal village in northeastern Brazil known for its sand dunes, lagoons, and strong winds that make it a popular destination for kitesurfing and other beach tourism.
-
D.
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.
-
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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0643ddaa48190b3ea8061fc1d9dc4 |
completed | March 22, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5199612948190b5ab22cf401686c2 |
completed | March 26, 2026, 11:33 a.m. |
Created at: March 22, 2026, 4:27 p.m.