Triple

T20276180
Position Surface form Disambiguated ID Type / Status
Subject Mary in The Passion of the Christ E503021 entity
Predicate hasFilmRatingContext P102265 FINISHED
Object R (for The Passion of the Christ in the US) LITERAL 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: R (for The Passion of the Christ in the US) | Statement: [Mary in The Passion of the Christ, hasFilmRatingContext, R (for The Passion of the Christ in the US)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFilmRatingContext
Context triple: [Mary in The Passion of the Christ, hasFilmRatingContext, R (for The Passion of the Christ in the US)]
  • A. hasFilmScoreBy
    Indicates that a film’s musical score was composed or created by a specified person or entity.
  • B. hasFilmScore
    Indicates that one entity serves as the musical score or soundtrack composed for a particular film.
  • C. hasFilmRatingAustralia
    Indicates that an entity (typically a film or audiovisual work) has a specific official classification or rating assigned by the Australian film rating system.
  • D. hasFilmRatingSystemIssueWith
    Indicates that there is a problem, conflict, or inconsistency involving a particular film rating system in relation to another entity.
  • E. ageRatingContext chosen
    Indicates the contextual basis or circumstances (such as region, system, or criteria) under which an age rating is assigned or interpreted.
  • F. None of above.

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_69e0b4b0e79c8190bd61f22ef1329fa8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e675e3df68819096fb859bc92a0da1 completed April 20, 2026, 6:52 p.m.
PD Predicate disambiguation batch_69e55b1e5e1c8190ba8a5544b1db9e1d completed April 19, 2026, 10:45 p.m.
Created at: April 16, 2026, 10:32 a.m.