Triple

T13369863
Position Surface form Disambiguated ID Type / Status
Subject Your Highness E319032 entity
Predicate starring P1507 FINISHED
Object Zooey Deschanel E148184 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: Zooey Deschanel | Statement: [Your Highness, starring, Zooey Deschanel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zooey Deschanel
Context triple: [Your Highness, starring, Zooey Deschanel]
  • A. Zooey Deschanel chosen
    Zooey Deschanel is an American actress, singer, and songwriter known for her quirky, offbeat roles in films like "500 Days of Summer" and the TV series "New Girl."
  • B. Amanda Peet
    Amanda Peet is an American actress known for her work in films like "The Whole Nine Yards" and television series such as "Studio 60 on the Sunset Strip" and "Togetherness."
  • C. Kaley Cuoco
    Kaley Cuoco is an American actress best known for her comedic television roles, particularly as Penny on the hit sitcom "The Big Bang Theory."
  • D. Anna Kendrick
    Anna Kendrick is an American actress and singer known for her versatile performances in films such as "Pitch Perfect," "Up in the Air," and the musical fantasy "Into the Woods."
  • E. Amanda Seyfried
    Amanda Seyfried is an American actress and singer known for her roles in films such as "Mamma Mia!", "Les Misérables," and "Mean Girls."
  • 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_69d806b7bbac8190b85278c87fa7aff3 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dadcd79184819088948cd38d10a4a5 completed April 11, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7942242cc8190aa94efae75370328 completed May 3, 2026, 6:29 p.m.
Created at: April 9, 2026, 9:33 p.m.