Triple

T5741260
Position Surface form Disambiguated ID Type / Status
Subject Something Borrowed E126618 entity
Predicate castMember P1668 FINISHED
Object Kate Hudson E242672 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: Kate Hudson | Statement: [Something Borrowed, castMember, Kate Hudson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Hudson
Context triple: [Something Borrowed, castMember, Kate Hudson]
  • A. Kate Hudson chosen
    Kate Hudson is an American actress known for her roles in romantic comedies and dramas, including her performance in the 2010 crime film "The Killer Inside Me."
  • B. Jennifer Love Hewitt
    Jennifer Love Hewitt is an American actress and singer best known for her roles in 1990s and 2000s film and television, including the horror and teen drama genres.
  • C. Jessica Biel
    Jessica Biel is an American actress and producer known for her roles in the TV series "7th Heaven" and films such as "The Texas Chainsaw Massacre" and "The Illusionist."
  • D. Kate Bosworth
    Kate Bosworth is an American actress best known for her roles in films such as "Blue Crush" and "Superman Returns."
  • E. Rose Byrne
    Rose Byrne is an Australian actress known for her versatile performances in films such as Bridesmaids, Neighbors, and X-Men: First Class, as well as the TV series Damages.
  • 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_69c0083179548190b384b0bf3c08ca4d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0258382908190af8787feb1e5fbcd completed March 22, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e168ebc8190ba8cb1b3e1b074d5 completed March 22, 2026, 11:41 p.m.
Created at: March 22, 2026, 3:48 p.m.