Triple

T8687932
Position Surface form Disambiguated ID Type / Status
Subject Ammer E206209 entity
Predicate region P40 FINISHED
Object Ammergau
Ammergau is a picturesque region in the Bavarian Alps of Germany, known for its traditional villages, scenic landscapes, and cultural heritage.
 E752426 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: Ammergau | Statement: [Ammer, region, Ammergau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ammergau
Context triple: [Ammer, region, Ammergau]
  • A. Gimmelwald
    Gimmelwald is a small, traditional Swiss alpine village known for its dramatic mountain scenery and tranquil, car-free atmosphere in the Bernese Oberland.
  • B. Oberwald
    Oberwald is a Swiss alpine village in the canton of Valais, known as a gateway to high mountain passes and scenic railway routes in the upper Rhône valley.
  • C. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • D. Meiringen
    Meiringen is a Swiss alpine town in the Bernese Oberland, known for its dramatic mountain scenery, Reichenbach Falls, and association with Sherlock Holmes.
  • E. Seengen
    Seengen is a Swiss municipality in the canton of Aargau, known for its scenic location in the Seetal valley and proximity to Lake Hallwil.
  • 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: Ammergau
Triple: [Ammer, region, Ammergau]
Generated description
Ammergau is a picturesque region in the Bavarian Alps of Germany, known for its traditional villages, scenic landscapes, and cultural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ammergau
Target entity description: Ammergau is a picturesque region in the Bavarian Alps of Germany, known for its traditional villages, scenic landscapes, and cultural heritage.
  • A. Gimmelwald
    Gimmelwald is a small, traditional Swiss alpine village known for its dramatic mountain scenery and tranquil, car-free atmosphere in the Bernese Oberland.
  • B. Oberwald
    Oberwald is a Swiss alpine village in the canton of Valais, known as a gateway to high mountain passes and scenic railway routes in the upper Rhône valley.
  • C. Waldegg
    Waldegg is a locality in Switzerland situated along the route of the A3 motorway.
  • D. Meiringen
    Meiringen is a Swiss alpine town in the Bernese Oberland, known for its dramatic mountain scenery, Reichenbach Falls, and association with Sherlock Holmes.
  • E. Seengen
    Seengen is a Swiss municipality in the canton of Aargau, known for its scenic location in the Seetal valley and proximity to Lake Hallwil.
  • 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_69ca835481fc819084e33d3bc883bfa6 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5731cf08819082e0cbe0975b70bb completed March 31, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf288acb348190829e149a9089a0a1 completed April 3, 2026, 2:40 a.m.
NEDg Description generation batch_69cf2bcff84881908a7985fdf8189583 completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2ca1ddac8190a36367e6bba8e3c8 completed April 3, 2026, 2:57 a.m.
Created at: March 30, 2026, 6:33 p.m.