Triple

T11236121
Position Surface form Disambiguated ID Type / Status
Subject Three Colors: Blue E265944 entity
Predicate leadCharacter P1668 FINISHED
Object Julie E124624 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 | Statement: [Three Colors: Blue, leadCharacter, Julie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julie
Context triple: [Three Colors: Blue, leadCharacter, Julie]
  • A. Julie chosen
    Julie is a feminine given name of Latin origin, commonly used in many Western countries.
  • B. Janet
    Janet is a feminine given name commonly used in English-speaking countries, often associated with notable figures in entertainment and public life.
  • C. Marnie
    Marnie is a 1964 psychological thriller film directed by Alfred Hitchcock, starring Tippi Hedren and Sean Connery, about a troubled woman with a mysterious past and compulsive thieving.
  • D. Margo
    Margo is the responsible and intelligent eldest of Gru’s three adopted daughters in the Despicable Me franchise.
  • E. Margo
    Margo was a Mexican-American actress and dancer known for her work in Hollywood films of the 1930s and 1940s and for her later stage and television appearances.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e904cf888190826fc964f76b5cb2 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4f3eca6bc8190bc0640353a505ad5 completed April 19, 2026, 3:25 p.m.
Created at: April 8, 2026, 9:30 p.m.