Triple

T5371359
Position Surface form Disambiguated ID Type / Status
Subject North Hesse E108856 entity
Predicate hasCity P316 FINISHED
Object Witzenhausen E487665 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: Witzenhausen | Statement: [North Hesse, hasCity, Witzenhausen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Witzenhausen
Context triple: [North Hesse, hasCity, Witzenhausen]
  • A. Witzenhausen chosen
    Witzenhausen is a small town in northern Hesse, Germany, known for its cherry orchards and agricultural research institutions.
  • B. Vellinghausen
    Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
  • C. Borgholzhausen
    Borgholzhausen is a small town in North Rhine-Westphalia, Germany, known for its location on the Teutoburg Forest and its historical ties to the former County of Ravensberg.
  • D. Korbach
    Korbach is a historic town in the German state of Hesse, known as the district seat of Waldeck-Frankenberg and for its well-preserved medieval old town.
  • E. Weiterstadt
    Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86aa0f5c8190ba96554e75696f8e completed March 20, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf411955e8819082648e9a86fbaf7c completed March 22, 2026, 1:08 a.m.
Created at: March 20, 2026, 2:02 p.m.