Triple
T17442467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sierre/Siders railway station |
E424691
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Sierre |
—
|
NE NERFINISHED |
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: Sierre | Statement: [Sierre/Siders railway station, serves, Sierre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sierre Context triple: [Sierre/Siders railway station, serves, Sierre]
-
A.
Sierre
chosen
Sierre is a municipality and important regional center in the canton of Valais in southwestern Switzerland, known for its wine production and bilingual French-German culture.
-
B.
Alpu
Alpu is a town and district in northwestern Turkey known for its agricultural activities and location within Eskişehir Province.
-
C.
Sumapaz Massif
The Sumapaz Massif is a high Andean region in central Colombia best known for containing Sumapaz Páramo, the largest páramo (high-altitude tropical moorland) ecosystem in the world.
-
D.
Monchique
Monchique is a mountainous spa town in southern Portugal known for its lush forests, thermal springs, and panoramic views over the Algarve region.
-
E.
Sierra Menera
Sierra Menera is a mountain range in eastern Spain known for its iron ore deposits and location within the broader Iberian System.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44ff82bbc819095dd0621137da809 |
completed | April 19, 2026, 3:46 a.m. |
Created at: April 10, 2026, 5:47 a.m.