Triple

T5203512
Position Surface form Disambiguated ID Type / Status
Subject A Walk in the Woods E117451 entity
Predicate producer P490 FINISHED
Object Philip Steuer E238623 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: Philip Steuer | Statement: [A Walk in the Woods, producer, Philip Steuer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philip Steuer
Context triple: [A Walk in the Woods, producer, Philip Steuer]
  • A. Philip Steuer chosen
    Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
  • B. Michael Hecht
    Michael Hecht is the birth name of Michael Howard, a British Conservative politician who served as Leader of the Opposition and Home Secretary.
  • C. Michael Bergmann
    Michael Bergmann is an American analytic philosopher known for his work in epistemology, particularly on skepticism, justification, and religious epistemology.
  • D. Stephen Endlicher
    Stephen Endlicher was a 19th-century Austrian botanist and linguist known for his influential work in plant taxonomy and classification.
  • E. Fredric Steinkamp
    Fredric Steinkamp was an American film editor best known for his acclaimed work on major Hollywood productions, including the Oscar-winning epic "Out of Africa."
  • 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_69bd4463dd3c81909966123f20b79d57 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a46393c81908da08f4fbfb6147d completed March 20, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfe1423aa481909fd062c54779a3a2 completed March 22, 2026, 12:32 p.m.
Created at: March 20, 2026, 1:47 p.m.