Triple

T11194713
Position Surface form Disambiguated ID Type / Status
Subject Gießen E264892 entity
Predicate countrySubdivision P766 FINISHED
Object Hesse E14304 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: Hesse | Statement: [Gießen, countrySubdivision, Hesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hesse
Context triple: [Gießen, countrySubdivision, Hesse]
  • A. Hesse chosen
    Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main and its mix of urban centers, forests, and historic towns.
  • B. South Hesse
    South Hesse is a region in the southern part of the German state of Hesse that includes major urban and economic centers such as Darmstadt and the Rhine-Main area.
  • C. Kurhessen
    Kurhessen was a historical region in central Germany that formed the core territory of the Electorate of Hesse (Hesse-Kassel) within the Holy Roman Empire and later German states.
  • D. Greater Hesse
    Greater Hesse was a post–World War II administrative region in western Germany established by the U.S. occupation authorities, which later formed the core of the modern state of Hesse.
  • 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_69d6aa9eb9248190b20211772621b4bc completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8bf14e481908563b15790af4d20 completed April 9, 2026, 5:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483ec6ca8819082713a278c987756 completed April 19, 2026, 7:27 a.m.
Created at: April 8, 2026, 9:29 p.m.