Triple
T15692770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gornergrat Railway |
E380374
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Riffelberg
Riffelberg is a scenic mountain stop in the Swiss Alps near Zermatt, known for its panoramic views of the Matterhorn and surrounding peaks.
|
E1208965
|
NE FINISHED |
How this triple was built (4 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: Riffelberg | Statement: [Gornergrat Railway, hasStation, Riffelberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Riffelberg Context triple: [Gornergrat Railway, hasStation, Riffelberg]
-
A.
Siegsdorf
Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
-
B.
Sigmaringen
Sigmaringen is a historic town in southwestern Germany best known for its Hohenzollern castle and its role as a former seat of the Hohenzollern-Sigmaringen principality.
-
C.
Mundolsheim
Mundolsheim is a suburban commune in northeastern France, located just north of Strasbourg in the Bas-Rhin department of the Grand Est region.
-
D.
Satzvey
Satzvey is a village in western Germany best known for its medieval moated castle, Burg Satzvey, and its historical festivals.
-
E.
Münchberg
Münchberg is a town in the Upper Franconia region of Bavaria, Germany, known historically for its textile industry and as a local commercial center.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Riffelberg Triple: [Gornergrat Railway, hasStation, Riffelberg]
Generated description
Riffelberg is a scenic mountain stop in the Swiss Alps near Zermatt, known for its panoramic views of the Matterhorn and surrounding peaks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Riffelberg Target entity description: Riffelberg is a scenic mountain stop in the Swiss Alps near Zermatt, known for its panoramic views of the Matterhorn and surrounding peaks.
-
A.
Siegsdorf
Siegsdorf is a Bavarian town in southeastern Germany known for its scenic Alpine surroundings and proximity to the Chiemsee lake.
-
B.
Sigmaringen
Sigmaringen is a historic town in southwestern Germany best known for its Hohenzollern castle and its role as a former seat of the Hohenzollern-Sigmaringen principality.
-
C.
Mundolsheim
Mundolsheim is a suburban commune in northeastern France, located just north of Strasbourg in the Bas-Rhin department of the Grand Est region.
-
D.
Satzvey
Satzvey is a village in western Germany best known for its medieval moated castle, Burg Satzvey, and its historical festivals.
-
E.
Münchberg
Münchberg is a town in the Upper Franconia region of Bavaria, Germany, known historically for its textile industry and as a local commercial center.
- F. None of above. chosen
Provenance (5 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f4f5a888190bd3681bcb9bbc02f |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d966ffc8190aa0d9d3abf8ad593 |
completed | May 10, 2026, 7:02 a.m. |
| NEDg | Description generation | batch_6a002ec2fd948190878af958d0b90ce6 |
completed | May 10, 2026, 7:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00312a4fc48190b6bd6ad9db71bb4d |
completed | May 10, 2026, 7:18 a.m. |
Created at: April 10, 2026, 4:44 a.m.