Triple

T12877785
Position Surface form Disambiguated ID Type / Status
Subject Leipzig metropolitan region E308012 entity
Predicate containsCity P294 FINISHED
Object Lützen E222931 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: Lützen | Statement: [Leipzig metropolitan region, containsCity, Lützen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lützen
Context triple: [Leipzig metropolitan region, containsCity, Lützen]
  • A. Lützen chosen
    Lützen is a town in present-day Germany best known as the site of the 1632 Battle of Lützen during the Thirty Years' War, where Swedish King Gustavus Adolphus was killed.
  • B. Altranstädt
    Altranstädt is a village in Saxony, Germany, historically notable as the site of early 18th-century treaties during the Great Northern War.
  • C. Schneidemühl
    Schneidemühl was a former German town (now Piła in Poland) that historically served as an important regional administrative and railway center.
  • D. Zeuthen
    Zeuthen is a municipality in Brandenburg, Germany, known for hosting a major campus of the DESY particle physics research center.
  • E. Pegnitz
    Pegnitz is a river in the German state of Bavaria that flows through cities such as Nuremberg and Bayreuth before joining the Rednitz to form the Regnitz.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69bb83bac8190838f7537b806317c completed May 3, 2026, 12:50 a.m.
Created at: April 9, 2026, 5:38 p.m.