Triple
T14428171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Schaffhausen |
E357749
|
entity |
| Predicate | highestPoint |
P210
|
FINISHED |
| Object |
Hagen (mountain)
Hagen is a mountain in northern Switzerland that forms the highest elevation in the canton of Schaffhausen.
|
E1099908
|
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: Hagen (mountain) | Statement: [canton of Schaffhausen, highestPoint, Hagen (mountain)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hagen (mountain) Context triple: [canton of Schaffhausen, highestPoint, Hagen (mountain)]
-
A.
Hangelsberg
Hangelsberg is a village in the German state of Brandenburg, known as a district of the municipality Grünheide (Mark) in the Oder-Spree region.
-
B.
Hagen Mountains
The Hagen Mountains are a rugged limestone mountain range in the Northern Limestone Alps of Austria, forming part of the Berchtesgaden Alps near the Salzach River.
-
C.
Schneidhain
Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
-
D.
Hohenthann
Hohenthann is a rural municipality in Lower Bavaria, Germany, known for its agricultural character and location within the Landshut district.
-
E.
Habach
Habach is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural character and Alpine foothill setting.
- 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: Hagen (mountain) Triple: [canton of Schaffhausen, highestPoint, Hagen (mountain)]
Generated description
Hagen is a mountain in northern Switzerland that forms the highest elevation in the canton of Schaffhausen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hagen (mountain) Target entity description: Hagen is a mountain in northern Switzerland that forms the highest elevation in the canton of Schaffhausen.
-
A.
Hangelsberg
Hangelsberg is a village in the German state of Brandenburg, known as a district of the municipality Grünheide (Mark) in the Oder-Spree region.
-
B.
Hagen Mountains
The Hagen Mountains are a rugged limestone mountain range in the Northern Limestone Alps of Austria, forming part of the Berchtesgaden Alps near the Salzach River.
-
C.
Schneidhain
Schneidhain is a district of the town Königstein im Taunus in the Hochtaunus region of Hesse, Germany.
-
D.
Hohenthann
Hohenthann is a rural municipality in Lower Bavaria, Germany, known for its agricultural character and location within the Landshut district.
-
E.
Habach
Habach is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural character and Alpine foothill setting.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91154de881909266ae88d1545685 |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bcfa1d88190b59cefd3e305f55f |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5d6af9ac8190a37f11b0f8a1db0f |
completed | May 8, 2026, 3:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5df48f7481909764bc4e23c0b04a |
completed | May 8, 2026, 3:52 a.m. |
Created at: April 10, 2026, 1:18 a.m.