Triple

T12600445
Position Surface form Disambiguated ID Type / Status
Subject Barmer Anlagen E300842 entity
Predicate locatedIn P40 FINISHED
Object Barmen E54311 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: Barmen | Statement: [Barmer Anlagen, locatedIn, Barmen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barmen
Context triple: [Barmer Anlagen, locatedIn, Barmen]
  • A. Barmen chosen
    Barmen is a historic industrial district in the German city of Wuppertal, known as a former textile and manufacturing center in the Ruhr region.
  • B. Brannenburg
    Brannenburg is a Bavarian municipality in southern Germany, known for its scenic Alpine setting and outdoor recreation opportunities.
  • C. Bornheim
    Bornheim is a lively residential and nightlife district in Frankfurt am Main, Germany, known for its traditional cider taverns, historic streets, and vibrant local culture.
  • D. Barmer
    Barmer is a prominent city in the western Indian state of Rajasthan, known for its desert landscape, handicrafts, and proximity to the Thar Desert.
  • E. Borken
    Borken is a town in western Germany that serves as an administrative and commercial center in the state of North Rhine-Westphalia.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954d1f6ac8190ab21ca7bcbc80129 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671926a7c8190a41725cfde7836b1 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:09 p.m.