Triple

T14277994
Position Surface form Disambiguated ID Type / Status
Subject Roger Aaron Brown E353962 entity
Predicate notableWork P4 FINISHED
Object Near Dark E268313 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: Near Dark | Statement: [Roger Aaron Brown, notableWork, Near Dark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Near Dark
Context triple: [Roger Aaron Brown, notableWork, Near Dark]
  • A. Near Dark chosen
    Near Dark is a 1987 neo-Western horror film that blends vampire mythology with gritty Americana and is widely regarded as an influential cult classic.
  • B. After the Dark
    After the Dark is a 2013 philosophical science-fiction thriller film that explores moral dilemmas through a series of apocalyptic thought experiments conducted by a high school philosophy class.
  • C. Darkest Before Dawn
    Darkest Before Dawn is a short film, likely a dramatic or suspenseful work, whose title evokes themes of struggle and hope before a turning point.
  • D. The Darkest Part
    "The Darkest Part" is a song by the American electronic music trio Cheat Codes.
  • E. The Darkest Dark
    The Darkest Dark is a children's picture book by astronaut Chris Hadfield that uses his childhood fear of the dark to inspire young readers to embrace curiosity and pursue their dreams.
  • 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_69d8278d25148190abf1a8c8f5f533ad completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6585270c8190a717127b2f5dab3b completed April 14, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd326f62b4819084b1e984678991ae completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:10 a.m.