Triple

T2129723
Position Surface form Disambiguated ID Type / Status
Subject Barely Lethal E46508 entity
Predicate starring P1507 FINISHED
Object Thomas Mann E294967 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: Thomas Mann | Statement: [Barely Lethal, starring, Thomas Mann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas Mann
Context triple: [Barely Lethal, starring, Thomas Mann]
  • A. Thomas Mann
    Thomas Mann was a German novelist, short story writer, and essayist renowned for works like "Buddenbrooks" and "The Magic Mountain," which explore the psychology and moral crises of modern European society.
  • B. Thomas Mann chosen
    Thomas Mann is an American actor known for his roles in films such as "Kong: Skull Island," "Project X," and "Me and Earl and the Dying Girl."
  • C. Heinrich Mann
    Heinrich Mann was a prominent German novelist and essayist known for his socially critical works and opposition to authoritarianism in the early 20th century.
  • D. Hermann Hess
    Hermann Hess was a mountaineer known for making the first recorded ascent of Monte San Valentín, the highest peak in Chilean Patagonia.
  • E. Heinrich Böll
    Heinrich Böll was a German writer and Nobel Prize–winning novelist known for his critical portrayals of postwar German society.
  • 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_69a88a1626548190ae59a5028c3baa8e completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbb77ccc4819087bee5dbb91b5ae8 completed March 7, 2026, 5:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce742d288190bfdcffb81c29a173 completed March 10, 2026, 7:55 a.m.
Created at: March 4, 2026, 7:44 p.m.