Triple

T8227511
Position Surface form Disambiguated ID Type / Status
Subject Federal Social Court of Germany E192208 entity
Predicate locatedInTheAdministrativeTerritorialEntity P40 FINISHED
Object Kassel E210960 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: Kassel | Statement: [Federal Social Court of Germany, locatedInTheAdministrativeTerritorialEntity, Kassel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kassel
Context triple: [Federal Social Court of Germany, locatedInTheAdministrativeTerritorialEntity, Kassel]
  • A. Kassel chosen
    Kassel is a city in central Germany known for its cultural institutions and as the host of the renowned contemporary art exhibition documenta.
  • B. Gießen
    Gießen is a mid-sized university city in central Germany known for its academic institutions and role as a regional administrative and cultural center.
  • C. Erfurt
    Erfurt is a historic German city in the state of Thuringia, known for its well-preserved medieval old town and as an important cultural and educational center.
  • D. Straußfurt
    Straußfurt is a municipality in the German state of Thuringia, known for its rural setting and proximity to the Unstrut River.
  • E. Wetzlar
    Wetzlar is a historic German city in the state of Hesse, known for its medieval old town and its long tradition in optics and precision engineering.
  • 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_69ca82db5b90819085d1ad7c2e27bfcc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb77fdcb048190868ea4995b020a37 completed March 31, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69d02f2a6ca88190b3f234447feab6e3 completed April 3, 2026, 9:20 p.m.
Created at: March 30, 2026, 5:46 p.m.