Triple

T13323421
Position Surface form Disambiguated ID Type / Status
Subject Ohm E317372 entity
Predicate locatedIn P40 FINISHED
Object Central Hesse E109575 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: Central Hesse | Statement: [Ohm, locatedIn, Central Hesse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Central Hesse
Context triple: [Ohm, locatedIn, Central Hesse]
  • A. Middle Hesse chosen
    Middle Hesse is a central region of the German state of Hesse known for its mix of historic university towns, industrial centers, and rural landscapes.
  • B. Upper Hesse
    Upper Hesse was a historical region in central Germany that formed the northern, upland part of the Landgraviate of Hesse-Darmstadt.
  • C. 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.
  • D. 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.
  • E. Hesse region
    Hesse region is a federal state in central-western Germany known for its financial hub Frankfurt am Main, forested landscapes, and historic cities such as Wiesbaden and Kassel.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9992c1fec8190bcb6a6bb3c973a24 completed April 11, 2026, 12:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7266cfb3c8190ac9ccb7696d02922 completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 9:30 p.m.