Triple
T15647489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chur |
E376218
|
entity |
| Predicate | connectedByRailTo |
P848
|
FINISHED |
| Object | St. Moritz |
E113674
|
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: St. Moritz | Statement: [Chur, connectedByRailTo, St. Moritz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. Moritz Context triple: [Chur, connectedByRailTo, St. Moritz]
-
A.
St. Moritz
chosen
St. Moritz is a famous Swiss alpine resort town renowned for its luxury tourism, winter sports, and role as a two-time Winter Olympics host.
-
B.
Gstaad
Gstaad is an upscale Swiss alpine resort village renowned for its luxury hotels, skiing, and exclusive social scene.
-
C.
Arosa
Arosa is a Swiss alpine resort town in the canton of Graubünden, known for its skiing, hiking, and scenic mountain landscapes.
-
D.
Zermatt
Zermatt is a renowned Swiss alpine resort village in the canton of Valais, famous for its skiing, mountaineering, and proximity to iconic peaks like the Matterhorn.
-
E.
Klosters
Klosters is a renowned Swiss Alpine village and ski resort in the canton of Graubünden, popular for its picturesque scenery and winter sports.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ed5b8b081908d7127964eed3b09 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67936e388190913c9060194e5b53 |
completed | May 9, 2026, 4:57 p.m. |
Created at: April 10, 2026, 4:15 a.m.