Triple
T12826657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linha do Vouga |
E306668
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Espinho |
E699875
|
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: Espinho | Statement: [Linha do Vouga, terminus, Espinho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Espinho Context triple: [Linha do Vouga, terminus, Espinho]
-
A.
Espinho
chosen
Espinho is a coastal city and municipality in northern Portugal, known for its beaches, casino, and traditional fishing heritage.
-
B.
Carvoeiro
Carvoeiro is a picturesque coastal village in southern Portugal known for its dramatic cliffs, sandy beaches, and role as a popular holiday destination.
-
C.
Sernancelhe
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
-
D.
Porto Covo
Porto Covo is a small coastal village in Portugal’s Alentejo region, known for its picturesque beaches, rugged cliffs, and traditional whitewashed houses.
-
E.
Sertã
Sertã is a municipality and town in central Portugal known for its forested landscapes, river beaches, and traditional cuisine.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96fae51608190a50970bd038359a5 |
completed | April 10, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ed4f7388190ba989b8a79bd7c6d |
completed | May 2, 2026, 11:55 p.m. |
Created at: April 9, 2026, 5:33 p.m.