Triple
T13097040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osasco |
E310616
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Santana de Parnaíba |
E297770
|
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: Santana de Parnaíba | Statement: [Osasco, borderedBy, Santana de Parnaíba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santana de Parnaíba Context triple: [Osasco, borderedBy, Santana de Parnaíba]
-
A.
Santana de Parnaíba
chosen
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.
-
B.
Baião
Baião is a Portuguese wine subregion within Vinho Verde, known for producing fresh, aromatic white wines, often from the Avesso grape.
-
C.
Cariri
Cariri is a microregion in the state of Ceará, Brazil, known for its cultural heritage, religious tourism, and distinctive semi-arid landscapes.
-
D.
Guararema
Guararema is a Brazilian municipality in the state of São Paulo, known for its preserved historic center, riverside landscapes, and eco-tourism attractions.
-
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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9814e88a0819088418c792ce7aa57 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a227d2c81908da0089d0e0387c6 |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:04 p.m.