Triple

T5054265
Position Surface form Disambiguated ID Type / Status
Subject Lay Lady Lay E113859 entity
Predicate hasCoverVersionBy P11142 FINISHED
Object Cher E92362 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: Cher | Statement: [Lay Lady Lay, hasCoverVersionBy, Cher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cher
Context triple: [Lay Lady Lay, hasCoverVersionBy, Cher]
  • A. Cher
    Cher is a department in central France, named after the Cher River and known for its historic towns, vineyards, and agricultural landscapes.
  • B. Cher chosen
    Cher is an American singer, actress, and pop culture icon known for her distinctive contralto voice, decades-spanning career, and hits like "Believe" and "If I Could Turn Back Time."
  • C. Cyndi Grecco
    Cyndi Grecco is an American singer best known for performing the upbeat 1970s television theme song "Making Our Dreams Come True" from the sitcom Laverne & Shirley.
  • D. Olivia Newton-John
    Olivia Newton-John was a British-Australian singer and actress best known for her role as Sandy in the film musical "Grease" and for hit songs such as "Physical."
  • E. Bette Midler
    Bette Midler is an American singer, actress, and comedian renowned for her powerful vocals, theatrical performances, and acclaimed work in film, television, and on stage.
  • 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_69bd443aa1f88190abb992d138f2cf42 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd742a59448190918766c261cfa13d completed March 20, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea489eb4c8190ad3a5480b909ef70 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:38 p.m.