Triple

T16381256
Position Surface form Disambiguated ID Type / Status
Subject Soest district E397811 entity
Predicate locatedBetween P1262 FINISHED
Object Sauerland E232082 NE FINISHED

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: Sauerland | Statement: [Soest district, locatedBetween, Sauerland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sauerland
Context triple: [Soest district, locatedBetween, Sauerland]
  • A. Sauerland chosen
    Sauerland is a hilly, forested region in western Germany known for its reservoirs, outdoor recreation, and winter sports areas.
  • B. Weser Uplands
    The Weser Uplands is a hilly, forested region in central Germany known for its picturesque landscapes, traditional half-timbered towns, and association with many of the Brothers Grimm fairy tales.
  • C. Lüneburg Heath
    Lüneburg Heath is a large heath and nature reserve in northern Germany known for its purple heather landscapes, historic villages, and protected wildlife habitats.
  • D. Weser-Leine Uplands
    The Weser-Leine Uplands are a hilly landscape region in central Germany characterized by forested ridges, river valleys, and diverse natural and cultural features.
  • E. Odenwald
    Odenwald is a low mountain range in southwestern Germany known for its forested hills, historic towns, and scenic hiking landscapes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e319dd0e0c8190812bde6a2f7d9644 completed April 18, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035689ef08190ba980a359498ca56 completed May 10, 2026, 7:36 a.m.
Created at: April 10, 2026, 5:08 a.m.