Triple

T4953517
Position Surface form Disambiguated ID Type / Status
Subject 1. FC Heidenheim E111224 entity
Predicate mainSponsor P737 FINISHED
Object Voith E111223 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: Voith | Statement: [1. FC Heidenheim, mainSponsor, Voith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Voith
Context triple: [1. FC Heidenheim, mainSponsor, Voith]
  • A. Voith chosen
    Voith is a German multinational engineering company known for its technologies and services in sectors such as energy, paper, raw materials, and transportation.
  • B. Bühler
    Bühler is a German-language surname borne by various notable individuals across fields such as politics, sports, and academia.
  • C. Deutz AG
    Deutz AG is a German manufacturer best known for producing internal combustion engines, particularly for industrial and agricultural applications.
  • D. Ebara
    Ebara is a district within Tokyo’s Shinagawa ward, known as a primarily residential area with local shopping streets and traditional neighborhoods.
  • E. Erla Maschinenwerk
    Erla Maschinenwerk was a German aircraft manufacturing company best known for producing Messerschmitt fighter planes under license during World War II.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71b82dd88190adfb08c3b3191fe0 completed March 20, 2026, 4:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9244fb008190baee4ade5b00691f completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:31 p.m.