Triple
T18986133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montijo |
E464562
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Vendas Novas |
—
|
NE NERFINISHED |
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: Vendas Novas | Statement: [Montijo, borderedBy, Vendas Novas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vendas Novas Context triple: [Montijo, borderedBy, Vendas Novas]
-
A.
Vendas Novas
chosen
Vendas Novas is a Portuguese town and municipality in the Alentejo region, known for its strategic location between Lisbon and Évora and its traditional bifanas (pork sandwiches).
-
B.
Currais Novos
Currais Novos is a municipality in the interior of the Brazilian state of Rio Grande do Norte, known for its semi-arid climate, livestock farming, and mineral resources.
-
C.
Morada Nova
Morada Nova is a municipality in the state of Ceará in northeastern Brazil, known for its agricultural activities and semi-arid landscape.
-
D.
Morrinhos
Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
-
E.
Estância Velha
Estância Velha is a municipality in the state of Rio Grande do Sul in southern Brazil, known historically for its leather and footwear industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65f7f08819088f56e8e030851b1 |
completed | April 20, 2026, 7:31 a.m. |
Created at: April 10, 2026, 12:01 p.m.