Triple

T7377104
Position Surface form Disambiguated ID Type / Status
Subject Schönhausen E170153 entity
Predicate locatedIn P40 FINISHED
Object Jerichower Land E650799 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: Jerichower Land | Statement: [Schönhausen, locatedIn, Jerichower Land]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerichower Land
Context triple: [Schönhausen, locatedIn, Jerichower Land]
  • A. Jerichower Land chosen
    Jerichower Land is a rural district in the German state of Saxony-Anhalt, known for its small towns, agricultural landscape, and location along the Elbe River.
  • 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. Havelland
    Havelland is a rural district in western Brandenburg, Germany, known for its river landscapes along the Havel, historic towns, and agricultural character.
  • D. Jerichow
    Jerichow is a small historic town in the German state of Saxony-Anhalt, known for its well-preserved Romanesque monastery complex.
  • E. Rübeland
    Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
  • 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_69c68a5bfaac81909ce7f001dfb70c76 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1a8b18c8190ad1a19521eda2319 completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802d15a8481908e43701459607276 completed March 28, 2026, 4:33 p.m.
Created at: March 27, 2026, 3:07 p.m.