Triple

T6134878
Position Surface form Disambiguated ID Type / Status
Subject The Blue Gardenia E136807 entity
Predicate screenwriter P2831 FINISHED
Object Charles Hoffman E396442 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: Charles Hoffman | Statement: [The Blue Gardenia, screenwriter, Charles Hoffman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Hoffman
Context triple: [The Blue Gardenia, screenwriter, Charles Hoffman]
  • A. Charles Hoffman chosen
    Charles Hoffman is a relatively obscure individual whose specific notability is not clearly identifiable from the given information alone.
  • B. Thomas Hoffman
    Thomas Hoffman is a relatively obscure individual whose name is shared with several people across different professions, making it difficult to attribute a single widely recognized identity to him.
  • C. William Hoffman
    William Hoffman is a relatively common personal name shared by multiple notable individuals across fields such as literature, politics, and the arts.
  • D. Paul Hoffman
    Paul Hoffman is a common name shared by several notable individuals, including authors, journalists, and public figures across various fields.
  • E. Thomas F. Hofmann
    Thomas F. Hofmann is a German food chemist and academic leader who serves as president of the Technical University of Munich.
  • 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_69c008a179388190a3b5a081bbf46d55 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05c80a6088190a028967b682fed2b completed March 22, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c62d035e9c8190bd9978987833ff3c completed March 27, 2026, 7:08 a.m.
Created at: March 22, 2026, 4:15 p.m.