Triple

T22013683
Position Surface form Disambiguated ID Type / Status
Subject Smithsonian Institution identity (via firm) E543647 entity
Predicate designer P184 FINISHED
Object Tom Geismar 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: Tom Geismar | Statement: [Smithsonian Institution identity (via firm), designer, Tom Geismar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Geismar
Context triple: [Smithsonian Institution identity (via firm), designer, Tom Geismar]
  • A. Tom Geismar chosen
    Tom Geismar is an American graphic designer renowned for his pioneering work in corporate identity and logo design, including co-founding the influential design firm Chermayeff & Geismar.
  • B. Josh Duhon
    Josh Duhon is an American actor best known for his role as Logan Hayes on the soap opera "General Hospital."
  • C. Mark Breland
    Mark Breland is an American former professional boxer and 1984 Olympic gold medalist in the welterweight division, later known as a respected boxing trainer.
  • D. Josh Sitton
    Josh Sitton is a former American football guard best known for his Pro Bowl career with the Green Bay Packers in the NFL.
  • E. Stephen Broussard
    Stephen Broussard is a film producer best known for his work on Marvel Cinematic Universe projects, including multiple Ant-Man films.
  • 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_69e11e2db934819095556760c7d85e4d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127a6bf6081909865781ea7937a1b completed April 28, 2026, 9:33 p.m.
Created at: April 16, 2026, 8:22 p.m.