Triple

T22530284
Position Surface form Disambiguated ID Type / Status
Subject Roth district E557013 entity
Predicate hasMunicipality P847 FINISHED
Object Greding NE NERFINISHED

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: Greding | Statement: [Roth district, hasMunicipality, Greding]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greding
Context triple: [Roth district, hasMunicipality, Greding]
  • A. Greding chosen
    Greding is a historic town in Bavaria, Germany, known for its well-preserved medieval city walls and location within the Altmühl Valley Nature Park.
  • B. Nesselried
    Nesselried is a village and district of the municipality of Appenweier in the Ortenau region of Baden-Württemberg, Germany.
  • C. Geretsried
    Geretsried is a town in Upper Bavaria, Germany, situated on the Isar River and known as the largest town in the Bad Tölz-Wolfratshausen district.
  • D. Kreuth
    Kreuth is a Bavarian municipality in southern Germany, known for its alpine landscape and location near Lake Tegernsee in the Bavarian Alps.
  • E. Gilching
    Gilching is a Bavarian municipality near Munich known for its residential character, local industry, and proximity to the Ammersee and Lake Starnberg recreation areas.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e57483c8190b0887c4f8ff26446 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ed6734881908abbbee477dfab98 completed April 29, 2026, 1:28 a.m.
Created at: April 16, 2026, 8:51 p.m.