Triple
T2642370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loulé railway station |
E62899
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Vilamoura |
E41622
|
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: Vilamoura | Statement: [Loulé railway station, locatedNear, Vilamoura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vilamoura Context triple: [Loulé railway station, locatedNear, Vilamoura]
-
A.
Vilamoura
chosen
Vilamoura is a major Portuguese resort town in the Algarve, known for its large marina, golf courses, beaches, and upscale tourist facilities.
-
B.
Albufeira
Albufeira is a popular coastal resort city in Portugal’s Algarve region, known for its beaches, nightlife, and tourism.
-
C.
Praia da Luz
Praia da Luz is a popular seaside resort village in Portugal’s Algarve region, known for its sandy beach, cliffs, and tourist-oriented waterfront.
-
D.
Portimão
Portimão is a coastal city and popular tourist destination in southern Portugal, known for its beaches, marina, and vibrant waterfront along the Arade River.
-
E.
Estoril
Estoril is a coastal resort town in the municipality of Cascais, Portugal, known for its beaches, casino, and historic role as a refuge for exiled royalty and political figures.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8ff34988190ba9d69ce9d77c71d |
completed | March 7, 2026, 7:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6352520819095eb04819578c1ba |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:53 p.m.