Triple

T4184337
Position Surface form Disambiguated ID Type / Status
Subject David Dolby E88273 entity
Predicate hasMother P1909 FINISHED
Object Dagmar Dolby E14337 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: Dagmar Dolby | Statement: [David Dolby, hasMother, Dagmar Dolby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dagmar Dolby
Context triple: [David Dolby, hasMother, Dagmar Dolby]
  • A. Dagmar Dolby chosen
    Dagmar Dolby is a philanthropist and widow of audio technology pioneer Ray Dolby, known for her significant charitable contributions, particularly in medical research and mental health.
  • B. Barbara Luddy
    Barbara Luddy was an American voice actress best known for her work in classic Disney animated films, including voicing the title character in "Lady and the Tramp."
  • C. Nora Dunn
    Nora Dunn is an American actress and comedian best known as a cast member on "Saturday Night Live" in the late 1980s and for her numerous film and television roles.
  • D. Joyce Kinney
    Joyce Kinney is a fictional news anchor character from the animated television series "Family Guy," where she works alongside Tom Tucker at the local TV station.
  • E. Debra Neil-Fisher
    Debra Neil-Fisher is an American film editor known for her work on major studio comedies and dramas, including entries in the Fifty Shades and The Hangover franchises.
  • 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0321eee88190871c1d4bf44a5007 completed March 9, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589fe4b508190a1c5a1d426245ede completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:45 p.m.