Triple

T4269115
Position Surface form Disambiguated ID Type / Status
Subject Angelus-Rosedale Cemetery E96896 entity
Predicate hasNotableBurial P196 FINISHED
Object Louise Fazenda E241210 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: Louise Fazenda | Statement: [Angelus-Rosedale Cemetery, hasNotableBurial, Louise Fazenda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louise Fazenda
Context triple: [Angelus-Rosedale Cemetery, hasNotableBurial, Louise Fazenda]
  • A. Louise Fazenda chosen
    Louise Fazenda was a prominent American silent film comedian and character actress known for her work in early Hollywood comedies.
  • B. Mariana Keil
    Mariana Keil is known primarily as a daughter of the Portuguese composer and painter Alfredo Keil, who wrote the music for Portugal’s national anthem.
  • C. Jacqueline Cambas
    Jacqueline Cambas is a film editor known for her work on the movie "Now and Then."
  • D. Laura Lopes
    Laura Lopes is a British art curator and gallery co-founder, best known as the daughter of Queen Camilla and her first husband, Andrew Parker Bowles.
  • E. Julie Bovasso
    Julie Bovasso was an American actress, playwright, and director best known for her character roles in films like "Moonstruck" and her influential work in avant-garde theater.
  • 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_69b34543f06c8190915ebb1a4574ffa9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ff913608190b6ccf4a85057b07b completed March 12, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c71c9b488190abbca16d3ea70ae8 completed March 14, 2026, 8:37 p.m.
Created at: March 12, 2026, 11:07 p.m.