Triple

T3240152
Position Surface form Disambiguated ID Type / Status
Subject Downhill E67946 entity
Predicate producer P490 FINISHED
Object Stefanie Azpiazu E348400 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: Stefanie Azpiazu | Statement: [Downhill, producer, Stefanie Azpiazu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stefanie Azpiazu
Context triple: [Downhill, producer, Stefanie Azpiazu]
  • A. Stefanie Azpiazu chosen
    Stefanie Azpiazu is a film producer known for her work on independent and character-driven movies, including the romantic comedy-drama "Enough Said."
  • B. Marta Ornelas
    Marta Ornelas is a Mexican former opera singer and stage director best known as the longtime wife of renowned Spanish tenor Plácido Domingo.
  • C. Mayte Garcia
    Mayte Garcia is an American dancer, choreographer, and actress best known for her work with and marriage to the musician Prince.
  • D. Jessica Garza
    Jessica Garza is an American actress best known for her prominent role in the television adaptation of the horror franchise "The Purge."
  • E. Tatiana Gutierrez
    Tatiana Gutierrez is a recurring nurse character in The Evil Within survival horror video game series, serving as a mysterious guide and save-point attendant for the protagonist within the STEM world.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaef6430081909084589f6eea5c7e completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b324f1baec8190b076b65fd7e4be2a completed March 12, 2026, 8:41 p.m.
Created at: March 8, 2026, 3:08 p.m.