Triple

T4075484
Position Surface form Disambiguated ID Type / Status
Subject Frankenderby E86754 entity
Predicate mainParticipants P2434 FINISHED
Object 1. FC Nürnberg E41334 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: 1. FC Nürnberg | Statement: [Frankenderby, mainParticipants, 1. FC Nürnberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 1. FC Nürnberg
Context triple: [Frankenderby, mainParticipants, 1. FC Nürnberg]
  • A. 1. FC Nürnberg chosen
    1. FC Nürnberg is a historic German football club based in Nuremberg, known for its multiple national championships and strong traditional fan base.
  • B. TSV 1860 Munich
    TSV 1860 Munich is a historic German football club from Munich known for its traditional fan base and past success in the Bundesliga.
  • C. 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.
  • D. Eintracht Frankfurt
    Eintracht Frankfurt is a professional German football club best known for competing in the Bundesliga and winning multiple domestic and European titles.
  • E. 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.
  • 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_69aed93ebe448190a1f1686e28740ac9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc25e2e08190b3c048e1b8f85bbf completed March 9, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5960443c48190901c674d2e947cef completed March 14, 2026, 5:08 p.m.
Created at: March 9, 2026, 3:39 p.m.