Triple

T10519831
Position Surface form Disambiguated ID Type / Status
Subject Bretten E248135 entity
Predicate locatedInRegion P40 FINISHED
Object Kraichgau E402336 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: Kraichgau | Statement: [Bretten, locatedInRegion, Kraichgau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kraichgau
Context triple: [Bretten, locatedInRegion, Kraichgau]
  • A. Kraichgau chosen
    Kraichgau is a hilly, fertile region in southwestern Germany known for its agriculture, vineyards, and picturesque landscapes between the Black Forest and the Odenwald.
  • B. Löwenberger Land
    Löwenberger Land is a rural municipality in the Oberhavel district of Brandenburg, Germany, known for its agricultural landscape and small villages north of Berlin.
  • C. Schwanfeld
    Schwanfeld is a small municipality in the Lower Franconia region of Bavaria, Germany, known for its rural character and historical roots.
  • D. Hellenstein
    Hellenstein is the historical namesake associated with Hellenstein Castle, a prominent medieval fortress in Heidenheim, Germany.
  • E. Röthlein
    Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509de0b3081909bec337aa8ff193e completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90e063e948190b2f7cbae05d9ea61 completed April 10, 2026, 2:49 p.m.
Created at: April 6, 2026, 12:28 p.m.