Triple

T15984449
Position Surface form Disambiguated ID Type / Status
Subject Brněnec E387656 entity
Predicate hasGermanName P1435 FINISHED
Object Brünnlitz E383744 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: Brünnlitz | Statement: [Brněnec, hasGermanName, Brünnlitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brünnlitz
Context triple: [Brněnec, hasGermanName, Brünnlitz]
  • A. Brünnlitz chosen
    Brünnlitz is a village in the Czech Republic best known as the location of Oskar Schindler’s wartime factory where he employed and saved Jewish workers during the Holocaust.
  • B. Gößnitz
    Gößnitz is a small town in the German state of Thuringia that lies within the broader Leipzig metropolitan area.
  • C. Olbernhau
    Olbernhau is a town in Germany’s Ore Mountains renowned for its traditional woodcraft industry, especially the production of Schwibbogen candle arches and other Christmas decorations.
  • D. Premnitz
    Premnitz is a small town in the Havelland region of Brandenburg, Germany, situated on the Havel River and known historically for its chemical industry.
  • E. Kühnitzsch
    Kühnitzsch is a village-level subdivision of the town of Wurzen in the German state of Saxony.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15757a3548190900de1962308f6b8 completed April 16, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00179fc28481909e1c46af343676ff completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 4:54 a.m.