Triple

T6619081
Position Surface form Disambiguated ID Type / Status
Subject Henry Minsky E149628 entity
Predicate hasRelative P367 FINISHED
Object Margaret Minsky E221745 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: Margaret Minsky | Statement: [Henry Minsky, hasRelative, Margaret Minsky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret Minsky
Context triple: [Henry Minsky, hasRelative, Margaret Minsky]
  • A. Margaret Minsky chosen
    Margaret Minsky is an American computer scientist and researcher known for her work in human-computer interaction and educational technology, and as the daughter of AI pioneer Marvin Minsky.
  • B. Margaret Shenberg
    Margaret Shenberg was the first wife of influential Hollywood film producer and studio executive Louis B. Mayer.
  • C. Juliana Minsky
    Juliana Minsky is a daughter of pioneering artificial intelligence researcher Marvin Minsky.
  • D. Rosalyn Tureck
    Rosalyn Tureck was an American pianist and harpsichordist renowned for her pioneering, intellectually rigorous interpretations of Johann Sebastian Bach’s keyboard works.
  • E. Margaret Sherman
    Margaret Sherman was the wife of prominent American architect and urban planner Daniel Burnham, known for her role within Chicago’s elite social circles during the late 19th and early 20th centuries.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af5ca97481909f8a7dc47249b4d3 completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a62bf8c8190b4b24b543e9095fa completed March 28, 2026, 12:01 a.m.
Created at: March 27, 2026, 1:58 p.m.