Triple

T2346284
Position Surface form Disambiguated ID Type / Status
Subject Margaret Blagge E45137 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: [Margaret Blagge, givenName, Margaret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margaret
Context triple: [Margaret Blagge, givenName, Margaret]
  • A. Margaret chosen
    Margaret is a feminine given name of Greek origin, traditionally associated with the meaning "pearl" and widely used in English-speaking countries.
  • B. 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.
  • 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 is one of Gru’s adopted daughters in the Despicable Me franchise, recognizable by her pink hat and mischievous, tomboyish personality.
  • 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_69a88917935081909b755dbf38e81024 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc6c9396081908abb2b0a229bb046 completed March 7, 2026, 6:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69aeb3c116088190b15fd12d5ac75594 completed March 9, 2026, 11:49 a.m.
Created at: March 4, 2026, 7:52 p.m.