Triple

T483865
Position Surface form Disambiguated ID Type / Status
Subject Bette Midler E9830 entity
Predicate fullName P16 FINISHED
Object Bette Midler E9830 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: Bette Midler | Statement: [Bette Midler, fullName, Bette Midler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bette Midler
Context triple: [Bette Midler, fullName, Bette Midler]
  • A. Bette Midler chosen
    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.
  • B. Barbra Streisand
    Barbra Streisand is an acclaimed American singer, actress, and filmmaker known for her powerful voice, award-winning performances, and enduring influence on popular culture.
  • C. Liza Minnelli
    Liza Minnelli is an American actress and singer best known for her Academy Award-winning performance in the film "Cabaret" and her powerful stage presence in musical theatre and concerts.
  • D. Ginny Newhart
    Ginny Newhart was an American homemaker and the longtime wife of comedian and actor Bob Newhart, known for her behind-the-scenes influence on his career and for inspiring key ideas in his television work.
  • E. Cher
    Cher is a department in central France, named after the Cher River and known for its historic towns, vineyards, and agricultural landscapes.
  • 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_69a2e802e2908190ab17c9479e0b6412 completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f0ba310c81909645ef7e8a20b52f completed Feb. 28, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a474701340819096a5073155af9625 completed March 1, 2026, 5:16 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.