Triple

T16443196
Position Surface form Disambiguated ID Type / Status
Subject Ghajini E399357 entity
Predicate censorRating P102265 FINISHED
Object U/A (India) 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: U/A (India) | Statement: [Ghajini, censorRating, U/A (India)]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: censorRating
Context triple: [Ghajini, censorRating, U/A (India)]
  • A. ratedFor
    Indicates that an entity has been evaluated and assigned a suitability or quality level for a particular purpose, context, or audience.
  • B. ageRatingContext chosen
    Indicates the contextual basis or circumstances (such as region, system, or criteria) under which an age rating is assigned or interpreted.
  • C. USRating
    Indicates that an entity has been assigned a rating, classification, or evaluation according to a United States–based standard or system.
  • D. CPVRating
    Indicates a content rating relationship that specifies the level of suitability or restriction of some media or material according to the CPV rating system.
  • E. mpaaRating
    Indicates the official Motion Picture Association of America (MPAA) content rating assigned to a film or audiovisual work.
  • 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_69d87f2c6778819080fcfae53be8f12a completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32cd8d2988190acb5722a15623319 completed April 18, 2026, 7:03 a.m.
PD Predicate disambiguation batch_69e227048d608190a4205eae3117629a completed April 17, 2026, 12:26 p.m.
Created at: April 10, 2026, 5:10 a.m.