Triple

T14805296
Position Surface form Disambiguated ID Type / Status
Subject Ol Parker E348018 entity
Predicate notableWork P4 FINISHED
Object Imagine Me & You E629857 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: Imagine Me & You | Statement: [Ol Parker, notableWork, Imagine Me & You]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Imagine Me & You
Context triple: [Ol Parker, notableWork, Imagine Me & You]
  • A. Imagine Me & You chosen
    Imagine Me & You is a 2005 British romantic comedy film about an unexpected love that blossoms between a newly married woman and a female florist she meets on her wedding day.
  • B. Imagine Me
    "Imagine Me" is a contemporary gospel song by Kirk Franklin that reflects on healing, self-acceptance, and freedom from past hurts.
  • C. Imagine You and Me
    Imagine You and Me is a Filipino romantic film best known for starring the popular love team of Alden Richards and Maine Mendoza.
  • D. You and Me
    "You and Me" is a song featured on the soundtrack of the farming simulation video game Harvest Moon.
  • E. You and Me
    "You and Me" is a Soviet drama film by acclaimed director Larisa Shepitko, exploring complex human relationships and moral choices.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decf32666081908e84f985c47eb963 completed April 14, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24c6b3008190a0fac1dace40361a completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:34 a.m.