Triple
T15491035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Borba |
E378684
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Vila Viçosa |
E195641
|
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: Vila Viçosa | Statement: [Borba, locatedNear, Vila Viçosa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vila Viçosa Context triple: [Borba, locatedNear, Vila Viçosa]
-
A.
Vila Viçosa
chosen
Vila Viçosa is a historic town in Portugal renowned for its marble quarries and as a former residence of the Portuguese royal family.
-
B.
Vila Flor
Vila Flor is a municipality in northern Portugal, situated in the Douro region known for its wine production and scenic landscapes.
-
C.
Vila Prudente
Vila Prudente is a metro station in São Paulo, Brazil, serving as a key terminal and transfer point on the city’s rapid transit network.
-
D.
Vila do Porto
Vila do Porto is the main town and oldest settlement in the Azores, located on Santa Maria Island in Portugal.
-
E.
Vila Verde
Vila Verde is a municipality in the Braga District of northern Portugal, known for its rural landscapes and traditional Minho culture.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fac2af88190ac1d119e6b21dbe0 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff365f27c48190822254b6da504d3d |
completed | May 9, 2026, 1:27 p.m. |
Created at: April 10, 2026, 3:48 a.m.