Triple

T15402788
Position Surface form Disambiguated ID Type / Status
Subject Norbert Wiener E368365 entity
Predicate spouse P13 FINISHED
Object Margaret Engemann 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: Margaret Engemann | Statement: [Norbert Wiener, spouse, Margaret Engemann]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret Engemann
Context triple: [Norbert Wiener, spouse, Margaret Engemann]
  • A. Margaret Engemann chosen
    Margaret Engemann was the wife of pioneering American mathematician and cybernetics founder Norbert Wiener.
  • B. Margaret Lindauer
    Margaret Lindauer is an individual notable enough to be recognized as a prominent bearer of the surname Lindauer.
  • C. Margaret Ann Knudsen
    Margaret Ann Knudsen, better known by her stage name Peggy Knudsen, was an American film, radio, and television actress active primarily in the 1940s and 1950s.
  • D. Margaret C. Etter
    Margaret C. Etter was an influential American chemist and crystallographer known for pioneering work in hydrogen bonding and crystal engineering.
  • E. Marjorie Vattendahl
    Marjorie Vattendahl was the wife of World War II flying ace and Medal of Honor recipient Richard Bong.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e8ea0ac8190a5c68b1951ad3db1 completed April 16, 2026, 1:42 a.m.
Created at: April 10, 2026, 3:19 a.m.