Triple

T11052340
Position Surface form Disambiguated ID Type / Status
Subject Jens Blauert E261286 entity
Predicate workLocation P7 FINISHED
Object Bochum E248839 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: Bochum | Statement: [Jens Blauert, workLocation, Bochum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bochum
Context triple: [Jens Blauert, workLocation, Bochum]
  • A. Bochum chosen
    Bochum is a major city in Germany’s Ruhr region known for its industrial heritage, cultural institutions, and large university.
  • B. Gelsenkirchen
    Gelsenkirchen is a city in western Germany known for its strong football culture and modern stadium, Veltins-Arena, home to FC Schalke 04.
  • C. Krefeld
    Krefeld is a city in western Germany near the Rhine River, known historically for its textile and silk industry.
  • D. Recklinghausen
    Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
  • E. Mülheim an der Ruhr
    Mülheim an der Ruhr is a city in western Germany’s Ruhr area, known for its industrial heritage, riverside setting on the Ruhr River, and role as a regional economic and cultural center.
  • 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_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7986c0df88190b29d71db5538450a completed April 9, 2026, 12:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69f018324bf88190bcd2bf168b1065d3 completed April 28, 2026, 2:15 a.m.
Created at: April 8, 2026, 9:26 p.m.