Triple

T11440340
Position Surface form Disambiguated ID Type / Status
Subject County of Mansfeld E271127 entity
Predicate capital P234 FINISHED
Object Mansfeld E432347 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: Mansfeld | Statement: [County of Mansfeld, capital, Mansfeld]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mansfeld
Context triple: [County of Mansfeld, capital, Mansfeld]
  • A. Mansfeld chosen
    Mansfeld is a small town in the German state of Saxony-Anhalt, historically known as a mining center and for its association with Martin Luther’s early life.
  • B. Lankwitz
    Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
  • C. Riedenburg
    Riedenburg is a small Bavarian town in southern Germany known for its scenic location in the Altmühl Valley and its historic castles.
  • D. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • E. Görlitz
    Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
  • 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_69d6aadeef688190874bcecd88b3dd9b completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d80888190c8190b6365550ffe4931c completed April 9, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69f08f409d348190ba97ed5cf34d755a completed April 28, 2026, 10:43 a.m.
Created at: April 8, 2026, 9:35 p.m.