Triple

T4342669
Position Surface form Disambiguated ID Type / Status
Subject A6 E97819 entity
Predicate connectsRegion P845 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: [A6, connectsRegion, Hesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hesse
Context triple: [A6, connectsRegion, 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. Rübeland
    Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
  • E. Odenwald
    Odenwald is a low mountain range in southwestern Germany known for its forested hills, historic towns, and scenic hiking landscapes.
  • 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_69b34548402c819085ab68b27c235a87 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351878c148190b384053479d41caf completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db9193c08190a6a63b82f604ecde completed March 14, 2026, 10:05 p.m.
Created at: March 12, 2026, 11:14 p.m.