Triple

T5842058
Position Surface form Disambiguated ID Type / Status
Subject Deutsche Börse E129616 entity
Predicate headquartersLocation P62 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: [Deutsche Börse, headquartersLocation, Hesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hesse
Context triple: [Deutsche Börse, headquartersLocation, 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034d876fc819089818c731116af56 completed March 22, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b0f371008190b11cd4da8a55dbb9 completed March 23, 2026, 3:18 a.m.
Created at: March 22, 2026, 3:54 p.m.