Triple

T2369794
Position Surface form Disambiguated ID Type / Status
Subject Weta Digital E46059 entity
Predicate formerName P65 FINISHED
Object Weta Ltd E46059 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: Weta Ltd | Statement: [Weta Digital, formerName, Weta Ltd]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weta Ltd
Context triple: [Weta Digital, formerName, Weta Ltd]
  • A. Weta Workshop
    Weta Workshop is a New Zealand-based special effects and prop design studio renowned for its groundbreaking work on major fantasy and science-fiction films.
  • B. Weta Digital chosen
    Weta Digital is a renowned New Zealand-based visual effects studio best known for its groundbreaking CGI work on major films such as The Lord of the Rings trilogy, Avatar, and the Planet of the Apes series.
  • C. Eon Productions
    Eon Productions is a British film production company best known for producing the long-running James Bond movie franchise.
  • D. Lucasfilm
    Lucasfilm is a renowned American film and television production company best known for creating the Star Wars and Indiana Jones franchises.
  • E. Annapurna Studios
    Annapurna Studios is a prominent Indian film production and post-production company based in Hyderabad, widely recognized for its role in shaping Telugu cinema.
  • 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_69a88a145268819083e2736cb835c696 completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc76dcaa481908567a068bd61e5ad completed March 7, 2026, 6:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf3294d88190be67aa4cca72bbb4 completed March 9, 2026, 12:38 p.m.
Created at: March 4, 2026, 7:56 p.m.