Triple
T13266010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linha de Guimarães |
E315925
|
entity |
| Predicate | startStation |
P389
|
FINISHED |
| Object | Porto-São Bento |
E1003756
|
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: Porto-São Bento | Statement: [Linha de Guimarães, startStation, Porto-São Bento]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Porto-São Bento Context triple: [Linha de Guimarães, startStation, Porto-São Bento]
-
A.
Porto São Bento
chosen
Porto São Bento is a historic railway station in Porto, Portugal, renowned for its ornate azulejo tile panels and central role in the city’s commuter and regional rail network.
-
B.
Porto dos Casais
Porto dos Casais was the original colonial settlement that later developed into the Brazilian city of Porto Alegre.
-
C.
Bemposta
Bemposta is a civil parish located within the municipality of Abrantes in central Portugal.
-
D.
Três Pontões
Três Pontões is a locality in the Brazilian state of Espírito Santo, known for its rural landscape and proximity to distinctive rocky formations.
-
E.
Morrinhos
Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
- 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9901e44bc8190966f87ae219d6bf4 |
completed | April 11, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a4ad79c8190b1304942dc48c0ff |
completed | May 3, 2026, 8:41 a.m. |
Created at: April 9, 2026, 9:25 p.m.