Triple

T22276547
Position Surface form Disambiguated ID Type / Status
Subject Rice University Duncan Hall E550622 entity
Predicate architect P184 FINISHED
Object Thomas Beeby 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: Thomas Beeby | Statement: [Rice University Duncan Hall, architect, Thomas Beeby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thomas Beeby
Context triple: [Rice University Duncan Hall, architect, Thomas Beeby]
  • A. Thomas Beeby chosen
    Thomas Beeby is an American architect associated with the New Classical movement, known for designing prominent cultural and institutional buildings.
  • B. Basil Henson
    Basil Henson was a British actor known for his work in film, television, and theatre during the mid-20th century.
  • C. Douglas Cockerell
    Douglas Cockerell was a prominent British bookbinder and teacher, renowned for his influential work in fine binding and book conservation in the early 20th century.
  • D. Paul Beeston
    Paul Beeston is a prominent Canadian baseball executive best known for his long tenure as a top leader of the Toronto Blue Jays and as the first president of Major League Baseball.
  • E. John Lapworth
    John Lapworth is a British film and sound editor known for his work on several notable feature films and television productions.
  • 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_69e11e44d538819097c6b8f333af3352 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14ea8a6688190bcd168670420ec59 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.