Triple

T22434078
Position Surface form Disambiguated ID Type / Status
Subject Freedom Writers E554571 entity
Predicate editedBy P1954 FINISHED
Object David Moritz NE NERFINISHED

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: David Moritz | Statement: [Freedom Writers, editedBy, David Moritz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Moritz
Context triple: [Freedom Writers, editedBy, David Moritz]
  • A. David Moritz chosen
    David Moritz is a film editor known for his work on notable movies including "The Life Aquatic with Steve Zissou."
  • B. Eduard Meyer
    Eduard Meyer was a prominent German historian and classical scholar known for his influential works on ancient history and historiography.
  • C. Johann David Michaelis
    Johann David Michaelis was an 18th-century German biblical scholar and orientalist known for his influential work in Hebrew and Old Testament studies.
  • D. Gustav Bauer
    Gustav Bauer was a German Social Democratic politician who served as Chancellor during the early Weimar Republic.
  • E. Johann Burkhard Mencke
    Johann Burkhard Mencke was a German scholar and literary figure of the late 17th and early 18th centuries, known for his contributions to philology and his influence within the intellectual life of Leipzig.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15adce9688190992ad0ca15883931 completed April 29, 2026, 1:11 a.m.
Created at: April 16, 2026, 8:47 p.m.