Triple

T2025302
Position Surface form Disambiguated ID Type / Status
Subject Southern Germany E44192 entity
Predicate hasLandscapeFeature P1094 FINISHED
Object Black Forest E15351 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: Black Forest | Statement: [Southern Germany, hasLandscapeFeature, Black Forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Black Forest
Context triple: [Southern Germany, hasLandscapeFeature, Black Forest]
  • A. Black Forest chosen
    The Black Forest is a large, densely wooded mountain range in southwestern Germany known for its picturesque villages, cuckoo clocks, and origin of the Danube River.
  • B. Palatinate Forest
    The Palatinate Forest is a large low-mountain forested region in southwestern Germany, known for its extensive woodlands, sandstone rock formations, and status as a protected nature park.
  • C. Rhön
    Rhön is a low mountain range in central Germany known for its volcanic landscape, open plateaus, and designation as a UNESCO Biosphere Reserve.
  • D. Harz
    Harz is a low mountain range in central Germany known for its dense forests, mining history, and association with German folklore such as the Brocken and Walpurgis Night.
  • E. Hardtberg
    Hardtberg is a borough of the German city of Bonn, located in the western part of the city and comprising several residential and administrative districts.
  • 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_69a8891201bc8190aca837be6de41579 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8f3faa08190a48ae1355d6e009f completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae0afa82ac81908c3e3c60c5721536 completed March 8, 2026, 11:49 p.m.
Created at: March 4, 2026, 7:38 p.m.