Triple

T20253758
Position Surface form Disambiguated ID Type / Status
Subject Mark Lee E498626 entity
Predicate hasWork P6260 FINISHED
Object Paper Man 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: Paper Man | Statement: [Mark Lee, hasWork, Paper Man]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paper Man
Context triple: [Mark Lee, hasWork, Paper Man]
  • A. Paper Man chosen
    Paper Man is a 2009 independent dramedy film about a struggling writer who befriends a young girl while grappling with his imaginary superhero companion.
  • B. Handsome Man
    "Handsome Man" is a song featured on the album *Escapology* by British pop artist Robbie Williams.
  • C. Side Man
    Side Man is a Tony Award–winning Broadway play by Warren Leight that portrays the turbulent lives of jazz musicians and their families across several decades.
  • D. Perfect Man
    The Perfect Man is a central Sufi metaphysical concept describing the fully realized human who perfectly reflects divine attributes and serves as the spiritual axis of creation.
  • E. Perfect Man
    Perfect Man is a short story by J. G. Ballard that explores themes of identity, consumerism, and the commodification of human perfection.
  • 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_69da6275fa6c8190952924930adee150 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e673aa42348190852ae8313f4494ca completed April 20, 2026, 6:42 p.m.
Created at: April 11, 2026, 11:41 p.m.