Triple

T2653294
Position Surface form Disambiguated ID Type / Status
Subject Elizabeth Anscombe E53949 entity
Predicate givenName P17 FINISHED
Object Margaret E17722 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 | Statement: [Elizabeth Anscombe, givenName, Margaret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret
Context triple: [Elizabeth Anscombe, givenName, Margaret]
  • A. Margaret
    Margaret is a 2011 American drama film written and directed by Kenneth Lonergan, known for its complex portrayal of grief and moral responsibility following a tragic bus accident in New York City.
  • B. Margaret chosen
    Margaret is a feminine given name of Greek origin, traditionally associated with the meaning "pearl" and widely used in English-speaking countries.
  • C. Margaret Rose
    Margaret Rose, better known as Princess Margaret, was the younger sister of Queen Elizabeth II and a prominent British royal noted for her glamorous yet often controversial life.
  • D. Marjorie
    Marjorie is a feminine given name of French origin that has been widely used in English-speaking countries.
  • E. Edith
    Edith was the birth name of Edith of Scotland, an Anglo-Saxon–Norman noblewoman who became Queen consort of England as the first wife of King Henry I.
  • 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_69ab495e192081909c77b622e8e7e15a completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd93197f48190b04faf358b503204 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb674ed4c8190a398fccdbd30e9c2 completed March 10, 2026, 6:13 a.m.
Created at: March 6, 2026, 9:53 p.m.