Triple

T14609809
Position Surface form Disambiguated ID Type / Status
Subject Kurhessen E342926 entity
Predicate todayPartOf P35 FINISHED
Object Bundesland Hessen E157843 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: Bundesland Hessen | Statement: [Kurhessen, todayPartOf, Bundesland Hessen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bundesland Hessen
Context triple: [Kurhessen, todayPartOf, Bundesland Hessen]
  • A. state of Hesse chosen
    The state of Hesse is a federal state in central Germany known for its financial hub Frankfurt am Main, extensive forests, and significant cultural and economic influence.
  • B. Hamburg state
    Hamburg state is a federal state of Germany that consists primarily of the city of Hamburg, a major northern European port and cultural center.
  • C. Province of Hesse-Nassau
    The Province of Hesse-Nassau was a Prussian administrative province in western Germany formed in the 19th century that included territories such as Hesse-Kassel and parts of Nassau.
  • D. 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.
  • E. Hesse-Kassel
    Hesse-Kassel was a German principality known for supplying large numbers of Hessian mercenary troops to fight alongside the British during the American Revolutionary War.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44f0dd48190a78662b5998a6722 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94d22170819098df75754f5c12ab completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.