Triple

T11817371
Position Surface form Disambiguated ID Type / Status
Subject Holzminden E281035 entity
Predicate partOf P40 FINISHED
Object Weser Uplands E43282 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: Weser Uplands | Statement: [Holzminden, partOf, Weser Uplands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weser Uplands
Context triple: [Holzminden, partOf, Weser Uplands]
  • A. Weser Uplands chosen
    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.
  • B. 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.
  • 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. Sauerland
    Sauerland is a hilly, forested region in western Germany known for its reservoirs, outdoor recreation, and winter sports areas.
  • E. Weserbergland
    Weserbergland is a hilly, forested region in central Germany known for its picturesque landscapes along the Weser River and numerous historic towns.
  • 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_69d6ab26aae88190b2489efcb2a24234 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5e760988190b50d13bba5ef5b43 completed April 10, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f131cbf9708190ba8394fb3508b975 completed April 28, 2026, 10:16 p.m.
Created at: April 8, 2026, 9:42 p.m.