Triple

T12794836
Position Surface form Disambiguated ID Type / Status
Subject Renfield (2023 film) E305860 entity
Predicate featuresCharacter P626 FINISHED
Object Teddy Lobo E860656 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: Teddy Lobo | Statement: [Renfield (2023 film), featuresCharacter, Teddy Lobo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teddy Lobo
Context triple: [Renfield (2023 film), featuresCharacter, Teddy Lobo]
  • A. Ramon Tikaram chosen
    Ramon Tikaram is a British actor known for his work in television, film, and theatre, including prominent roles in UK drama series.
  • B. Hal Pereira
    Hal Pereira was a prominent American art director and production designer known for his influential visual work on numerous classic Hollywood films.
  • C. Dennis de Brito
    Dennis de Brito is known primarily as the husband of Dutch-born American actress Nina Foch.
  • D. Frank Pereira
    Frank Pereira is a researcher known for his work in machine learning and related fields, including collaborations with prominent scientists such as Léon Bottou.
  • E. Jerome Teelucksingh
    Jerome Teelucksingh is a Trinidadian academic and activist best known for reviving and promoting International Men's Day as a global observance focused on men's health, positive male role models, and gender relations.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6ca0288190aba01735b71a01da completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6850ac1808190a9b547d934252d10 completed May 2, 2026, 11:13 p.m.
Created at: April 9, 2026, 5:30 p.m.