Triple

T13081084
Position Surface form Disambiguated ID Type / Status
Subject Wałbrzych E310204 entity
Predicate hasTwinTown P919 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: [Wałbrzych, hasTwinTown, Freiberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Freiberg
Context triple: [Wałbrzych, hasTwinTown, 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_69d806a733548190989cfd4ce981ca33 completed April 9, 2026, 8:05 p.m.
NER Named-entity recognition batch_69d98119cb7081908b78ffe83ec99851 completed April 10, 2026, 11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f74cb388190836484a1dd7d1d67 completed May 3, 2026, 5:01 p.m.
Created at: April 9, 2026, 9:01 p.m.