Triple

T21947329
Position Surface form Disambiguated ID Type / Status
Subject Merkur Mountain E541966 entity
Predicate region P40 FINISHED
Object Southwest Germany NE NERFINISHED

How this triple was built (2 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: Southwest Germany | Statement: [Merkur Mountain, region, Southwest Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Southwest Germany
Context triple: [Merkur Mountain, region, Southwest Germany]
  • A. southwestern Germany chosen
    Southwestern Germany is a region of Germany known for its forested landscapes, wine-growing areas, and proximity to France and Switzerland.
  • B. South Hesse
    South Hesse is a region in the southern part of the German state of Hesse that includes major urban and economic centers such as Darmstadt and the Rhine-Main area.
  • C. Rhine-Weser region
    The Rhine-Weser region is a historical area in western Germany associated with the early homeland and formation of the Frankish people.
  • D. Upper Germany
    Upper Germany was a Roman imperial province along the upper Rhine frontier, encompassing parts of modern southwestern Germany, eastern France, and Switzerland.
  • E. southern Germany
    Southern Germany is a culturally and economically significant region of Germany known for its Alpine landscapes, historic cities, and strong regional identities such as Bavaria and Baden-Württemberg.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47ef0e48190a50e1bcc43f4b3fd completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12428dee48190acb63051ed7cd03e completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:57 p.m.