Triple

T12728213
Position Surface form Disambiguated ID Type / Status
Subject Lars Eidinger E304161 entity
Predicate name P16 FINISHED
Object Lars Eidinger E304161 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: Lars Eidinger | Statement: [Lars Eidinger, name, Lars Eidinger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lars Eidinger
Context triple: [Lars Eidinger, name, Lars Eidinger]
  • A. Lars Eidinger chosen
    Lars Eidinger is a German actor known for his work in both arthouse cinema and mainstream films, as well as for acclaimed stage performances at Berlin's Schaubühne theatre.
  • B. Christian Hebel
    Christian Hebel is an American violinist and concertmaster known for his work on Broadway productions, film scores, and live performances with prominent recording artists.
  • C. Andreas Scholl
    Andreas Scholl is a renowned German countertenor celebrated for his interpretations of Baroque and early music.
  • D. Uli Wiesendanger
    Uli Wiesendanger is an advertising executive best known as a co-founder of the global advertising agency network TBWA Worldwide.
  • E. Hannes Löhr
    Hannes Löhr was a German footballer and later coach, best known as a prolific forward for 1. FC Köln and as a member of the West Germany national team.
  • 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_69d7bdf1426c8190a4402e1c4cdec33a completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d964172490819080cd022ff8290b6e completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684e7dec08190b522a8f3bfde6fe2 completed May 2, 2026, 11:12 p.m.
Created at: April 9, 2026, 5:25 p.m.