Triple

T21041658
Position Surface form Disambiguated ID Type / Status
Subject Kit Kat Klub E518339 entity
Predicate notableSongContext P116848 FINISHED
Object Willkommen 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: Willkommen | Statement: [Kit Kat Klub, notableSongContext, Willkommen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Willkommen
Context triple: [Kit Kat Klub, notableSongContext, Willkommen]
  • A. Willkommen chosen
    "Willkommen" is the iconic opening number from the musical *Cabaret*, introducing the seedy, seductive world of the Kit Kat Klub and its enigmatic Emcee.
  • B. Benvenuto
    Benvenuto is an Italian masculine given name most famously borne by the Renaissance sculptor and goldsmith Benvenuto Cellini.
  • C. Bienvenues
    Bienvenues is a renowned component of the name of the prestigious Burgundy Grand Cru white wine Bienvenues-Bâtard-Montrachet.
  • D. Welkom
    Welkom is a South African city in the Free State province known historically for its gold mining industry and planned urban layout.
  • E. Bienvenüe
    Bienvenüe is a French surname most notably associated with Fulgence Bienvenüe, the engineer often called the "father" of the Paris Métro.
  • 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_69e0b50438e08190917e2538bb8bc034 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fcefe4688190ad1bed1ef2d7a3e5 completed April 21, 2026, 4:28 a.m.
Created at: April 16, 2026, 2:15 p.m.