Triple

T16048040
Position Surface form Disambiguated ID Type / Status
Subject Böblingen E389273 entity
Predicate locatedOn P40 FINISHED
Object Schönbuch forest edge E472991 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: Schönbuch forest edge | Statement: [Böblingen, locatedOn, Schönbuch forest edge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schönbuch forest edge
Context triple: [Böblingen, locatedOn, Schönbuch forest edge]
  • A. Wermsdorf Forest
    Wermsdorf Forest is a large woodland area in Saxony, Germany, known for its historic hunting grounds and scenic landscapes.
  • B. Schönbuch forest chosen
    Schönbuch forest is a large protected woodland and nature park in Baden-Württemberg, Germany, known for its diverse wildlife, hiking trails, and recreational areas near the city of Stuttgart.
  • C. Eichgestell forest area
    The Eichgestell forest area is a wooded section within Berlin’s Wuhlheide, known for its natural greenery and recreational walking paths.
  • D. Hallerbos forest
    Hallerbos forest is a renowned woodland in Belgium famous for its spectacular springtime carpet of blooming bluebells that draws visitors and photographers from around the world.
  • E. Arnsberg Forest
    Arnsberg Forest is a large wooded region in North Rhine-Westphalia, Germany, known for its extensive hiking trails, natural landscapes, and protected nature reserves.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18360464881909fd4d3bcb4ffb7f5 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbddc25481908fca660c4f14eaff completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:56 a.m.