Triple
T22349247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A10 motorway (Portugal) |
E552482
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Arruda dos Vinhos |
—
|
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: Arruda dos Vinhos | Statement: [A10 motorway (Portugal), passesNear, Arruda dos Vinhos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arruda dos Vinhos Context triple: [A10 motorway (Portugal), passesNear, Arruda dos Vinhos]
-
A.
Arruda dos Vinhos
chosen
Arruda dos Vinhos is a Portuguese municipality and wine-producing town located in the Lisbon metropolitan area.
-
B.
Figueiró dos Vinhos
Figueiró dos Vinhos is a municipality in central Portugal known for its forested landscapes, river beaches, and traditional rural character.
-
C.
Mondim de Basto
Mondim de Basto is a small town in northern Portugal known for its scenic mountainous landscapes and role as the administrative center of the surrounding municipality.
-
D.
Dão-Lafões
Dão-Lafões is a subregion in central Portugal known for its mountainous landscapes, thermal spas, and production of Dão wines.
-
E.
Póvoa de Penela
Póvoa de Penela is a civil parish located in the municipality of Penedono in Portugal.
- 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1579a1c308190ae2174f99ae317ab |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:43 p.m.