Triple

T480717
Position Surface form Disambiguated ID Type / Status
Subject Nollywood E9159 entity
Predicate rankAmongFilmIndustries P1944 FINISHED
Object one of the largest film producers in the world 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: one of the largest film producers in the world | Statement: [Nollywood, rankAmongFilmIndustries, one of the largest film producers in the world]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: rankAmongFilmIndustries
Context triple: [Nollywood, rankAmongFilmIndustries, one of the largest film producers in the world]
  • A. popularFilmIndustry
    Indicates that an entity has a widely recognized and well-liked film industry that attracts significant audience interest and attention.
  • B. foundingIndustry
    Indicates the industry or sector in which an entity was originally founded or began its primary operations.
  • C. mostAwardsFilm
    Indicates that a film is the one that has received the highest number of awards within a given set or context.
  • D. rankedAs chosen
    Indicates that one entity is assigned a specific position or level in an ordered ranking relative to others.
  • E. rankedBy
    Indicates that one entity is ordered or assigned a position in a hierarchy or list according to criteria determined or applied by another entity.
  • 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_69a2e7ff81708190b0507a24a997232c completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f058ebe48190aaa0a829b21f75fa completed Feb. 28, 2026, 1:40 p.m.
PD Predicate disambiguation batch_69a2edf321288190b5d560f75782c2cb completed Feb. 28, 2026, 1:30 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.