Triple

T20669679
Position Surface form Disambiguated ID Type / Status
Subject Werner Lorant E507986 entity
Predicate employer P7 FINISHED
Object TSV 1860 Munich NE NERFINISHED

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: TSV 1860 Munich | Statement: [Werner Lorant, employer, TSV 1860 Munich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TSV 1860 Munich
Context triple: [Werner Lorant, employer, TSV 1860 Munich]
  • A. TSV 1860 Munich chosen
    TSV 1860 Munich is a historic German football club from Munich known for its traditional fan base and past success in the Bundesliga.
  • B. Hertha BSC
    Hertha BSC is a professional football club from Berlin, Germany, that competes in the German league system and is one of the country’s oldest and most historic teams.
  • C. VfB Stuttgart
    VfB Stuttgart is a prominent German professional football club based in Stuttgart that competes in the Bundesliga and has a history of multiple national championships.
  • D. Hannover 96
    Hannover 96 is a professional German football club based in Hanover, best known for competing in the Bundesliga and having a long history dating back to the late 19th century.
  • E. 1. FC Nürnberg
    1. FC Nürnberg is a historic German football club based in Nuremberg, known for its multiple national championships and strong traditional fan base.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4c059bc81908ea762cd73ea4424 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6b5c735048190a01cb7692928d66e completed April 20, 2026, 11:24 p.m.
Created at: April 16, 2026, 11:44 a.m.