Triple

T17102551
Position Surface form Disambiguated ID Type / Status
Subject Lünen E415014 entity
Predicate partOf P40 FINISHED
Object Unna district E395574 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: Unna district | Statement: [Lünen, partOf, Unna district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unna district
Context triple: [Lünen, partOf, Unna district]
  • A. Unna district chosen
    Unna district is a Landkreis in the German state of North Rhine-Westphalia, located in the eastern Ruhr area and known for its mix of industrial towns and suburban communities.
  • B. Tillo District
    Tillo District is an administrative district in southeastern Turkey known for its historical and religious significance within Siirt Province.
  • C. Lillafüred district
    Lillafüred district is a scenic neighborhood of Miskolc in northeastern Hungary, known for its lakeside setting, historic hotel, and surrounding Bükk Mountains.
  • D. Hallunda district
    Hallunda district is a suburban residential area in Botkyrka Municipality, south of central Stockholm, Sweden.
  • E. Otyrar District
    Otyrar District is an administrative district in southern Kazakhstan, historically notable for encompassing the site of the ancient Silk Road city of Otyrar.
  • 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_69d886cfc8e88190b05ba466edd35591 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2495c88190b5b16a006a994faf completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139fdda488190a1ca5c7ca875e044 completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:35 a.m.