Triple

T9498817
Position Surface form Disambiguated ID Type / Status
Subject Weiden in der Oberpfalz E229081 entity
Predicate hasMayor P185 FINISHED
Object Jens Meyer E802089 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: Jens Meyer | Statement: [Weiden in der Oberpfalz, hasMayor, Jens Meyer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jens Meyer
Context triple: [Weiden in der Oberpfalz, hasMayor, Jens Meyer]
  • A. Jens Meyer chosen
    Jens Meyer is a German local politician who serves as the mayor of the Bavarian town of Weiden in der Oberpfalz.
  • B. Jens Beckert
    Jens Beckert is a German sociologist renowned for his work on economic sociology, particularly the role of expectations and uncertainty in markets.
  • C. Jens Christensen
    Jens Christensen is a relatively common Scandinavian personal name shared by multiple individuals across fields such as politics, sports, and academia.
  • D. Jens Schlosser
    Jens Schlosser is a cinematographer known for his work on the film "The Salvation."
  • E. Jens Toldstrup
    Jens Toldstrup was a prominent Danish resistance leader during World War II, known for organizing sabotage and intelligence operations against the German occupation.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd983a94c48190a7ddf95a953c4ecc completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a0a5ec881908bb1643d2bea2c9f completed April 4, 2026, 4:19 p.m.
Created at: March 30, 2026, 7:56 p.m.