Triple
T6214711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Urseren-Goms region |
E138956
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object |
Münster-Geschinen
Münster-Geschinen is a small alpine village in the Swiss canton of Valais, known for its traditional wooden houses and location in the upper Rhone valley.
|
E574805
|
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: Münster-Geschinen | Statement: [Urseren-Goms region, hasVillage, Münster-Geschinen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Münster-Geschinen Context triple: [Urseren-Goms region, hasVillage, Münster-Geschinen]
-
A.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
B.
Radevormwald
Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
-
C.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
D.
Waldbröl
Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
-
E.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
- 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: Münster-Geschinen Triple: [Urseren-Goms region, hasVillage, Münster-Geschinen]
Generated description
Münster-Geschinen is a small alpine village in the Swiss canton of Valais, known for its traditional wooden houses and location in the upper Rhone valley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Münster-Geschinen Target entity description: Münster-Geschinen is a small alpine village in the Swiss canton of Valais, known for its traditional wooden houses and location in the upper Rhone valley.
-
A.
Günsberg
Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
-
B.
Radevormwald
Radevormwald is a small historic town in North Rhine-Westphalia, western Germany, known for its hilly Bergisches Land landscape and traditional textile and metalworking industries.
-
C.
Gevelsberg
Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
-
D.
Waldbröl
Waldbröl is a small town in North Rhine-Westphalia, Germany, known for its rural setting in the Bergisches Land region.
-
E.
Bergkamen
Bergkamen is a town in North Rhine-Westphalia, Germany, known for its coal mining heritage and post-war planned urban development.
- 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_69c008ada364819096c9e92c74d639b5 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062a0e0488190b71b42386bacf982 |
completed | March 22, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c16f61ed708190a034136cc270e9d0 |
completed | March 23, 2026, 4:50 p.m. |
| NEDg | Description generation | batch_69c1bfb484ac8190903efdf4a18f3a1c |
completed | March 23, 2026, 10:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1c03551008190af5e3427b4cdcd11 |
completed | March 23, 2026, 10:35 p.m. |
Created at: March 22, 2026, 4:21 p.m.