Triple

T11630368
Position Surface form Disambiguated ID Type / Status
Subject Leonding E276379 entity
Predicate borderedBy P224 FINISHED
Object Wilhering E536985 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: Wilhering | Statement: [Leonding, borderedBy, Wilhering]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilhering
Context triple: [Leonding, borderedBy, Wilhering]
  • A. Wilhering chosen
    Wilhering is a municipality in Upper Austria, known for the historic Wilhering Abbey and its location near the city of Linz.
  • B. Weiler am Berge
    Weiler am Berge is a small village that forms one of the districts of the town of Mechernich in North Rhine-Westphalia, Germany.
  • C. Widdersberg
    Widdersberg is a small village that forms one of the local subdivisions of the municipality of Münsing in Bavaria, Germany.
  • D. Willenberg
    Willenberg is the former German name of the town now known as Wielbark, located in northern Poland.
  • E. 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.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a127b2688190ae3a340f851e834b completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ee87a20af481909b47775c7cb6ec3b completed April 26, 2026, 9:46 p.m.
Created at: April 8, 2026, 9:39 p.m.