Triple

T15722042
Position Surface form Disambiguated ID Type / Status
Subject Suhl E381119 entity
Predicate stateCapitalOf P6344 FINISHED
Object Bezirk Suhl E511489 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: Bezirk Suhl | Statement: [Suhl, stateCapitalOf, Bezirk Suhl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bezirk Suhl
Context triple: [Suhl, stateCapitalOf, Bezirk Suhl]
  • A. Bezirk Suhl chosen
    Bezirk Suhl was an administrative district in the former East Germany, located in the southern part of the country and known for its mountainous Thuringian landscape and industrial centers.
  • B. Bezirk Gera
    Bezirk Gera was an administrative district of the former East Germany, centered around the city of Gera in the state of Thuringia.
  • C. Bezirk Halle
    Bezirk Halle was an administrative district of the former East Germany, centered around the city of Halle and functioning as a key regional unit during the GDR era.
  • D. Eichsfeld district
    Eichsfeld district is a rural administrative district in northern Thuringia, Germany, known for its historically Catholic character within a largely Protestant region.
  • E. Bitterfeld district
    Bitterfeld district was a former administrative district in the German state of Saxony-Anhalt, known historically for its lignite mining and chemical industry.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fb0b51081908e652ec4992296fa completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb03539c081908b5df46bb810b949 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 4:45 a.m.