Triple

T6162306
Position Surface form Disambiguated ID Type / Status
Subject Andrea Sachs E137469 entity
Predicate loveInterest P7325 FINISHED
Object Nate Cooper E154684 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: Nate Cooper | Statement: [Andrea Sachs, loveInterest, Nate Cooper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nate Cooper
Context triple: [Andrea Sachs, loveInterest, Nate Cooper]
  • A. Nate Cooper chosen
    Nate Cooper is a character in the film "The Devil Wears Prada," known as the boyfriend of protagonist Andy Sachs who represents her pre-fashion-world life and values.
  • B. Nate Morgan
    Nate Morgan is a musician best known as a member of the American funk band Rufus.
  • C. Nate Ford
    Nate Ford is the brilliant but morally conflicted former insurance investigator who leads the crew of con artists in the television series "Leverage."
  • D. Nate Archibald
    Nate Archibald is a Hall of Fame NBA point guard renowned for leading the league in both scoring and assists in the same season and starring primarily for the Cincinnati/Kansas City Kings and Boston Celtics.
  • E. Nate Heller
    Nate Heller is a film composer and songwriter known for his emotionally resonant scores for movies such as "A Beautiful Day in the Neighborhood" and "Can You Ever Forgive Me?".
  • 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_69c008a54fc88190b6ce4416490ca79d completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d371484819090c18b62b095b49e completed March 22, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c14199f024819089af02b1c0eebfad completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:17 p.m.