Triple

T10548118
Position Surface form Disambiguated ID Type / Status
Subject Bertelsmann Stiftung E248874 entity
Predicate headquartersLocation P62 FINISHED
Object Gütersloh E486915 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: Gütersloh | Statement: [Bertelsmann Stiftung, headquartersLocation, Gütersloh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gütersloh
Context triple: [Bertelsmann Stiftung, headquartersLocation, Gütersloh]
  • A. Gütersloh chosen
    Gütersloh is a city in the German state of North Rhine-Westphalia known for being the headquarters of major companies like Bertelsmann and Miele.
  • B. Bielefeld
    Bielefeld is a major city in northwestern Germany known for its industrial heritage, university, and the tongue-in-cheek “Bielefeld conspiracy” meme claiming it does not exist.
  • C. Lippstadt
    Lippstadt is a historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
  • D. Osnabrück
    Osnabrück is a historic city in Lower Saxony, Germany, known for its medieval architecture and role in the Peace of Westphalia.
  • E. Detmold
    Detmold is a historic town in northwestern Germany that served as the capital and residence city of the former Principality of Lippe.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d526d305d081909b48d244e1cfa092 completed April 7, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c7b89a808190af9b2d4f37ad9012 completed April 18, 2026, 6:04 p.m.
Created at: April 6, 2026, 12:33 p.m.