Triple

T267843
Position Surface form Disambiguated ID Type / Status
Subject Metropolregion Mitteldeutschland E5771 entity
Predicate hasMember P10 FINISHED
Object Dessau-Roßlau E53961 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: Dessau-Roßlau | Statement: [Metropolregion Mitteldeutschland, hasMember, Dessau-Roßlau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dessau-Roßlau
Context triple: [Metropolregion Mitteldeutschland, hasMember, Dessau-Roßlau]
  • A. Anhalt-Zerbst
    Anhalt-Zerbst was a small principality within the Holy Roman Empire, historically notable as the homeland of Catherine the Great and a source of German auxiliary troops in the 18th century.
  • B. City of Dessau-Roßlau chosen
    The City of Dessau-Roßlau is a German city in Saxony-Anhalt known for its Bauhaus architectural heritage and role as an industrial and cultural center in central Germany.
  • C. Ronsdorf
    Ronsdorf is a district of the German city of Wuppertal in North Rhine-Westphalia, historically known as an independent town in the Bergisches Land region.
  • D. Leipzig
    Leipzig is a major city in eastern Germany known for its rich cultural heritage, vibrant music and arts scene, and important role in trade and commerce.
  • E. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • 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_69a2587daeb081909591b9d30f80a271 completed Feb. 28, 2026, 2:52 a.m.
NER Named-entity recognition batch_69a25dae4a0c8190a66cf6ed3889851c completed Feb. 28, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69a79273925c8190aba320775ef88061 completed March 4, 2026, 2:01 a.m.
Created at: Feb. 28, 2026, 2:56 a.m.