Triple

T10923461
Position Surface form Disambiguated ID Type / Status
Subject DASA E258003 entity
Predicate formedByMergerOf P77 FINISHED
Object MTU München E344833 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: MTU München | Statement: [DASA, formedByMergerOf, MTU München]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MTU München
Context triple: [DASA, formedByMergerOf, MTU München]
  • A. MTU München chosen
    MTU München was the original company from which MTU Aero Engines emerged, serving as a key German manufacturer in the aerospace and engine industry.
  • 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. TH Karlsruhe
    TH Karlsruhe is the traditional abbreviation for the University of Karlsruhe, a prominent German technical university known for its engineering and technology programs.
  • D. 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.
  • E. 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.
  • 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_69d6aa864ed88190818280ab6791d065 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7708e3fd881908da10f24a856364c completed April 9, 2026, 9:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2172894d88190b7b27f78e9fd1521 completed April 17, 2026, 11:19 a.m.
Created at: April 8, 2026, 9:22 p.m.