Triple

T8725582
Position Surface form Disambiguated ID Type / Status
Subject Magdalene Shaw E207121 entity
Predicate spouse P13 FINISHED
Object Mr. Shaw E400152 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: Mr. Shaw | Statement: [Magdalene Shaw, spouse, Mr. Shaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mr. Shaw
Context triple: [Magdalene Shaw, spouse, Mr. Shaw]
  • A. Mr. Shaw chosen
    Mr. Shaw is a wealthy, conservative Boston businessman who serves as the head of the household and a symbol of traditional values in Louisa May Alcott’s novel "An Old-Fashioned Girl."
  • B. Mr. Hawkins
    Mr. Hawkins is the father of Jim Hawkins, the young protagonist of Robert Louis Stevenson’s classic adventure novel "Treasure Island."
  • C. Mr. Fletcher
    Mr. Fletcher is the video store owner in the comedy film "Be Kind Rewind," around whose struggling VHS rental shop the movie’s events and homemade remakes revolve.
  • D. Vernon Shaw
    Vernon Shaw was a Dominican politician who served as the fifth President of the Commonwealth of Dominica from 1998 to 2003.
  • E. Mr. Hill
    Mr. Hill is the formal title used to address Marion Hill, likely in a professional or respectful social context.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d158b0481908249610458f97306 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf2912c4e08190a147fc31db6788d1 completed April 3, 2026, 2:42 a.m.
Created at: March 30, 2026, 6:36 p.m.