Triple

T4219542
Position Surface form Disambiguated ID Type / Status
Subject Rear Window E94305 entity
Predicate artDirectionBy P7743 FINISHED
Object Hal Pereira E224435 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: Hal Pereira | Statement: [Rear Window, artDirectionBy, Hal Pereira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hal Pereira
Context triple: [Rear Window, artDirectionBy, Hal Pereira]
  • A. Hal Pereira chosen
    Hal Pereira was a prominent American art director and production designer known for his influential visual work on numerous classic Hollywood films.
  • B. 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.
  • C. Henry Pereira Mendes
    Henry Pereira Mendes was a prominent 19th–20th century Sephardic rabbi and communal leader in the United States, known for his influential role in modern Orthodox Judaism and Jewish education.
  • D. Vaz Pinto
    Vaz Pinto is a Portuguese surname associated with figures such as Catarina de Almeida Vaz Pinto, a notable cultural and political personality in Portugal.
  • E. Dean Pereira
    Dean Pereira is a working-class husband and father whose troubled marriage and emotional unraveling form the core of the romantic drama film "Blue Valentine."
  • 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_69b3451997e08190851db4a9a588837d completed March 12, 2026, 10:58 p.m.
NER Named-entity recognition batch_69b34e0b2ee08190930600e1e802b325 completed March 12, 2026, 11:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5963d3bd8819086465701f4c6adf5 completed March 14, 2026, 5:09 p.m.
Created at: March 12, 2026, 11:04 p.m.