Triple

T20453020
Position Surface form Disambiguated ID Type / Status
Subject Do Revenge E501702 entity
Predicate castMember P1668 FINISHED
Object Paris Berelc NE NERFINISHED

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: Paris Berelc | Statement: [Do Revenge, castMember, Paris Berelc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris Berelc
Context triple: [Do Revenge, castMember, Paris Berelc]
  • A. Paris Berelc chosen
    Paris Berelc is an American actress and model best known for her roles in Disney XD and Netflix series, including action and comedy projects aimed at younger audiences.
  • B. André Bauma
    André Bauma is a Congolese park ranger renowned for his dedicated care and protection of orphaned mountain gorillas in Virunga National Park.
  • C. Bruno Barbey
    Bruno Barbey was a renowned French-Moroccan photojournalist celebrated for his vivid color photography and extensive work documenting political unrest and cultural life around the world.
  • D. Jules Sitruk
    Jules Sitruk is a French actor known for his early roles in films such as "Monsieur Batignole" and "Son of Rambow."
  • E. Marcel Berbert
    Marcel Berbert was a French film producer known for his collaborations with prominent directors such as François Truffaut during the mid-20th century.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ac0a1c81908845d0f8a56abce8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e68d039af08190827bf765b50515a8 completed April 20, 2026, 8:30 p.m.
Created at: April 16, 2026, 11:32 a.m.