Triple

T19807388
Position Surface form Disambiguated ID Type / Status
Subject Ivan Sutherland E475849 entity
Predicate spouse P13 FINISHED
Object Marsha Sutherland NE NERFINISHED

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: Marsha Sutherland | Statement: [Ivan Sutherland, spouse, Marsha Sutherland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marsha Sutherland
Context triple: [Ivan Sutherland, spouse, Marsha Sutherland]
  • A. Marsha Sutherland chosen
    Marsha Sutherland is known as the wife of pioneering computer scientist Ivan Sutherland.
  • B. Marilyn McLeod
    Marilyn McLeod was an American songwriter best known for co-writing several Motown hits, including Diana Ross’s disco classic “Love Hangover.”
  • C. Meryl Swanson
    Meryl Swanson is an Australian politician and member of the House of Representatives for the Labor Party.
  • D. Cathleen Neilson
    Cathleen Neilson was an American socialite known for her marriage into the wealthy Vanderbilt family through Reginald Claypoole Vanderbilt.
  • E. Annette Kirk
    Annette Kirk is an American cultural advocate and widow of conservative thinker Russell Kirk, known for promoting his intellectual legacy and traditionalist ideas through institutions such as the Kirk Center for Cultural Renewal.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65428f5c48190be6ae0d6a77675d2 completed April 20, 2026, 4:28 p.m.
Created at: April 10, 2026, 1:49 p.m.