Triple

T4016071
Position Surface form Disambiguated ID Type / Status
Subject Cecilia Peck E90762 entity
Predicate name P16 FINISHED
Object Cecilia Peck E90762 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: Cecilia Peck | Statement: [Cecilia Peck, name, Cecilia Peck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cecilia Peck
Context triple: [Cecilia Peck, name, Cecilia Peck]
  • A. Cecilia Peck chosen
    Cecilia Peck is an American actress, documentary filmmaker, and producer, and the daughter of legendary actor Gregory Peck.
  • B. Cecilia Parker
    Cecilia Parker was a Canadian-born American film actress best known for playing Marian Hardy, the sister of Mickey Rooney’s character, in the popular Andy Hardy film series of the 1930s and 1940s.
  • C. Vina Wray
    Vina Wray is an alternate name for Fay Wray, the Canadian-American actress best known for her iconic role in the 1933 film "King Kong."
  • D. Maysie Hoy
    Maysie Hoy is a Canadian film editor known for her work on numerous feature films, including collaborations with prominent directors such as Tyler Perry.
  • E. Myrna Dell
    Myrna Dell was an American film and television actress known for her roles in 1940s and 1950s Hollywood productions, particularly in film noir and B-movies.
  • 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_69aed95e44088190aff7d90a151b1b20 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefaa7352481908232534c89a698e7 completed March 9, 2026, 4:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b556295aa081908e803233b986fec9 completed March 14, 2026, 12:35 p.m.
Created at: March 9, 2026, 3:35 p.m.