Triple
T13266058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guimarães railway station |
E315926
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Famalicão |
E525928
|
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: Famalicão | Statement: [Guimarães railway station, connectsTo, Famalicão]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Famalicão Context triple: [Guimarães railway station, connectsTo, Famalicão]
-
A.
Porto-Campanhã
Porto-Campanhã is the main railway station in Porto, Portugal, serving as a central hub for long-distance and regional train services across the country.
-
B.
Sernancelhe
Sernancelhe is a municipality in northern Portugal known for its historic granite architecture, religious heritage, and scenic rural landscapes.
-
C.
Espinho
Espinho is a coastal city and municipality in northern Portugal, known for its beaches, casino, and traditional fishing heritage.
-
D.
Vila Nova de Famalicão
chosen
Vila Nova de Famalicão is a municipality in northern Portugal known for its strong industrial base, particularly in textiles and manufacturing.
-
E.
Carvoeiro
Carvoeiro is a picturesque coastal village in southern Portugal known for its dramatic cliffs, sandy beaches, and role as a popular holiday destination.
- 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_69fd5bad771881908280e3d96be068fc |
completed | May 8, 2026, 3:42 a.m. |
Created at: April 9, 2026, 9:25 p.m.