Triple

T19036679
Position Surface form Disambiguated ID Type / Status
Subject Danielle Harris E465889 entity
Predicate notableWork P4 FINISHED
Object Halloween 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: Halloween | Statement: [Danielle Harris, notableWork, Halloween]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Halloween
Context triple: [Danielle Harris, notableWork, Halloween]
  • A. Halloween
    "Halloween" is a dark, fan-favorite song by the Dave Matthews Band known for its intense emotion and rare live performances.
  • B. Halloween
    Halloween is an annual celebration observed on October 31, characterized by costumes, trick-or-treating, spooky decorations, and themes of the supernatural and the macabre.
  • C. Halloween chosen
    Halloween is a 1978 American slasher film directed by John Carpenter that helped define the horror genre and introduced the iconic character Michael Myers.
  • D. Trick or Treat
    "Trick or Treat" is a 1986 horror-comedy film about a heavy metal-obsessed teenager who unwittingly resurrects a dead rock star through a cursed record, directed by Charles Martin Smith.
  • E. One Halloween
    "One Halloween" is a song featured on the musical theatre album *Applause*.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d744b39881909334a80a4c15000b completed April 20, 2026, 7:35 a.m.
Created at: April 10, 2026, 12:02 p.m.