Triple
T20499035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triesenberg |
E503251
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Rotenboden
Rotenboden is a small settlement or locality within the mountainous municipality of Triesenberg in Liechtenstein.
|
E1434166
|
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: Rotenboden | Statement: [Triesenberg, contains, Rotenboden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rotenboden Context triple: [Triesenberg, contains, Rotenboden]
-
A.
Rotenboden
Rotenboden is a high-altitude railway station in the Swiss Alps, known as a scenic stop on the route to the Gornergrat with panoramic views of the Matterhorn and surrounding peaks.
-
B.
Kreuzboden
Kreuzboden is a popular alpine recreation area in the Swiss Alps above Saas-Grund, known for its scenic mountain views, hiking trails, and ski facilities.
-
C.
Bodenmais
Bodenmais is a Bavarian spa and holiday resort town in the Bavarian Forest of Germany, known for its glassmaking tradition and outdoor recreation.
-
D.
Todenfeld
Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
E.
Rottenegg
Rottenegg is a small village that forms one of the local subdivisions of the Bavarian town of Geisenfeld in Germany.
- 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: Rotenboden Triple: [Triesenberg, contains, Rotenboden]
Generated description
Rotenboden is a small settlement or locality within the mountainous municipality of Triesenberg in Liechtenstein.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rotenboden Target entity description: Rotenboden is a small settlement or locality within the mountainous municipality of Triesenberg in Liechtenstein.
-
A.
Rotenboden
Rotenboden is a high-altitude railway station in the Swiss Alps, known as a scenic stop on the route to the Gornergrat with panoramic views of the Matterhorn and surrounding peaks.
-
B.
Kreuzboden
Kreuzboden is a popular alpine recreation area in the Swiss Alps above Saas-Grund, known for its scenic mountain views, hiking trails, and ski facilities.
-
C.
Bodenmais
Bodenmais is a Bavarian spa and holiday resort town in the Bavarian Forest of Germany, known for its glassmaking tradition and outdoor recreation.
-
D.
Todenfeld
Todenfeld is a village and district of the town of Rheinbach in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
E.
Rottenegg
Rottenegg is a small village that forms one of the local subdivisions of the Bavarian town of Geisenfeld in Germany.
- 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_69e0b4b1e52c8190894281cf7e3283ab |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69cbff210819089900e9a35911f48 |
completed | April 20, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0893bd1c508190bbba38fb36650723 |
completed | May 16, 2026, 3:56 p.m. |
| NEDg | Description generation | batch_6a0894634f748190ae0a3be77125bf03 |
completed | May 16, 2026, 3:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08958072d08190a0e4ba12c7e550ea |
completed | May 16, 2026, 4:04 p.m. |
Created at: April 16, 2026, 11:35 a.m.