Triple

T1984053
Position Surface form Disambiguated ID Type / Status
Subject Martin Benrath E43097 entity
Predicate nameInNativeLanguage P1435 FINISHED
Object Martin Benrath E43097 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: Martin Benrath | Statement: [Martin Benrath, nameInNativeLanguage, Martin Benrath]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martin Benrath
Context triple: [Martin Benrath, nameInNativeLanguage, Martin Benrath]
  • A. Martin Benrath chosen
    Martin Benrath was a German actor known for his extensive work in film, television, and theater from the mid-20th century onward.
  • B. Eckhard Pfeiffer
    Eckhard Pfeiffer is a German-American businessman best known for serving as CEO of Compaq Computer Corporation during its rapid expansion in the 1990s.
  • C. Jürgen Büscher
    Jürgen Büscher is a screenwriter best known for co-writing the 1993 German war film "Stalingrad."
  • D. Ewald Loeser
    Ewald Loeser was a German lawyer and industrial executive who served in senior positions at the Krupp conglomerate and was later prosecuted for his role in Nazi-era crimes during the post–World War II Krupp Trial.
  • E. Jürgen Prochnow
    Jürgen Prochnow is a German actor best known internationally for his intense performances in films such as "Das Boot" and numerous Hollywood productions.
  • 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_69a88713ddc88190a969715658ebe7a8 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb820815481908aac6d89b437225b completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69b1de68338c8190bf28d0a51716623a completed March 11, 2026, 9:28 p.m.
Created at: March 4, 2026, 7:37 p.m.