Triple
T12313055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaguariúna |
E293529
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Pedreira |
E294684
|
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: Pedreira | Statement: [Jaguariúna, locatedNear, Pedreira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pedreira Context triple: [Jaguariúna, locatedNear, Pedreira]
-
A.
Pedreira
chosen
Pedreira is a municipality in the state of São Paulo, Brazil, known for its ceramics industry and decorative household goods.
-
B.
Capileira
Capileira is a picturesque mountain village in Spain’s Alpujarras region, known for its traditional whitewashed houses and dramatic location on the southern slopes of the Sierra Nevada.
-
C.
Cabeceiras de Basto
Cabeceiras de Basto is a small municipality in northern Portugal known for its rural landscapes, traditional Minho architecture, and cultural heritage.
-
D.
Achada do Teixeira
Achada do Teixeira is a popular mountain plateau and viewpoint in Madeira, Portugal, serving as a main access point for hikes into the island’s central highlands.
-
E.
Cabaceiras
Cabaceiras is a historic town in the Brazilian state of Paraíba, known for its well-preserved colonial architecture and frequent use as a filming location for movies and television.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f03d3c88190baedffb83465bff8 |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e86d45881909a9a3c09df0b78f1 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:53 p.m.