Triple

T6126705
Position Surface form Disambiguated ID Type / Status
Subject Water for Elephants E136612 entity
Predicate producer P490 FINISHED
Object Erwin Stoff E350670 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: Erwin Stoff | Statement: [Water for Elephants, producer, Erwin Stoff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Erwin Stoff
Context triple: [Water for Elephants, producer, Erwin Stoff]
  • A. Erwin Stoff chosen
    Erwin Stoff is a Hollywood film producer and talent manager known for overseeing major studio projects and guiding the careers of high-profile actors.
  • B. Erwin Bälz
    Erwin Bälz was a German internist and physiologist renowned for his pioneering contributions to modern medicine in Japan during the Meiji era.
  • C. Carl Schuhmann
    Carl Schuhmann was a German athlete renowned for winning multiple gold medals in gymnastics and wrestling at the inaugural modern Olympic Games in 1896.
  • D. Erwin Kurtz
    Erwin Kurtz is a person notable enough to be recognized as a significant bearer of the surname Kurtz.
  • E. Hans Pilger
    Hans Pilger is an individual notable enough to be recognized as a bearer of the surname Pilger, though specific widely known biographical details about him are not readily documented.
  • 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_69c008a0a37c81908e5b4f879158afb3 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05c2a13a48190b80e11d58fc87c8a completed March 22, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c603d90bcc81908f819a9e262ec17a completed March 27, 2026, 4:13 a.m.
Created at: March 22, 2026, 4:15 p.m.