Triple
T13266059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guimarães railway station |
E315926
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Vizela |
E1029849
|
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: Vizela | Statement: [Guimarães railway station, connectsTo, Vizela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vizela Context triple: [Guimarães railway station, connectsTo, Vizela]
-
A.
Vizela
Vizela is a Portuguese professional football club that competes in the country's top-tier league system.
-
B.
Vizela
chosen
Vizela is a town and municipality in northern Portugal known for its thermal baths and location in the Ave Valley region.
-
C.
Baia Mare
Baia Mare is a city in northwestern Romania known for its mining history, surrounding Carpathian landscapes, and role as an important regional cultural and economic center.
-
D.
Tecuci
Tecuci is a town in eastern Romania known as a local transport hub and administrative center in Galați County.
-
E.
Galați
Galați is a major Romanian port city in eastern Romania, situated near the border with Moldova and known for its shipbuilding and steel industries.
- 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_69f716cd8c2c8190a28d901fde98dc26 |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:25 p.m.