Triple

T2008985
Position Surface form Disambiguated ID Type / Status
Subject Julie & Julia E43648 entity
Predicate mainSubject P3 FINISHED
Object Julie Powell E351665 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: Julie Powell | Statement: [Julie & Julia, mainSubject, Julie Powell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julie Powell
Context triple: [Julie & Julia, mainSubject, Julie Powell]
  • A. Julie Powell chosen
    Julie Powell was an American writer and blogger best known for her memoir "Julie & Julia," which chronicled her year-long project of cooking every recipe in Julia Child’s "Mastering the Art of French Cooking."
  • B. Julie Alexander
    Julie Alexander is an American businesswoman and former wife of legendary television and radio host Larry King.
  • C. Julie Buck
    Julie Buck is a member of the Buck family, known primarily as a relative of American sportscaster Joe Buck.
  • D. Melissa Mathison
    Melissa Mathison was an American screenwriter best known for writing the screenplay for Steven Spielberg’s film "E.T. the Extra-Terrestrial."
  • E. Lori Collins
    Lori Collins is a central character in the comedy film "Ted," known as John Bennett’s long-suffering girlfriend who pushes him to grow up and choose between her and his crude, living teddy bear best friend.
  • 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_69a88716e9f08190946313fdc949e3cf completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb89be08c81909eb5ea672ea46b2b completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69b34ba4db388190baa1108563783227 completed March 12, 2026, 11:26 p.m.
Created at: March 4, 2026, 7:37 p.m.