Triple

T11687069
Position Surface form Disambiguated ID Type / Status
Subject Erzgebirge E277770 entity
Predicate contains P35 FINISHED
Object Freiberg E123043 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: Freiberg | Statement: [Erzgebirge, contains, Freiberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Freiberg
Context triple: [Erzgebirge, contains, Freiberg]
  • A. Freiberg chosen
    Freiberg is a historic mining town in eastern Germany renowned for its silver mining heritage and well-preserved medieval architecture.
  • B. Reichenberg
    Reichenberg is the former German name for the city of Liberec, a major urban center in the northern Czech Republic near the border with Germany and Poland.
  • C. Riesa
    Riesa is a town in the German state of Saxony, situated on the Elbe River and known historically as an important regional railway and industrial center.
  • D. 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.
  • E. Bischofswerda
    Bischofswerda is a small town in the Saxony region of eastern Germany, known as a local commercial and transport hub near the city of Dresden.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4654be881909bd0256cf18e25de completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69f08fd4c09081909ee36de77ca67247 completed April 28, 2026, 10:45 a.m.
Created at: April 8, 2026, 9:40 p.m.