Triple

T21448268
Position Surface form Disambiguated ID Type / Status
Subject Mark Carrier E529134 entity
Predicate name P16 FINISHED
Object Mark Carrier 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: Mark Carrier | Statement: [Mark Carrier, name, Mark Carrier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mark Carrier
Context triple: [Mark Carrier, name, Mark Carrier]
  • A. Mark Carrier chosen
    Mark Carrier is a former American football safety who played in the NFL, most notably for the Chicago Bears, and was known for his hard-hitting style and Pro Bowl-caliber play.
  • B. Stephen M. Kellen
    Stephen M. Kellen was a prominent financier and philanthropist known for his leadership at Arnhold and S. Bleichroeder and his significant support of cultural and educational institutions.
  • C. Mark C. Carnes
    Mark C. Carnes is an American historian and professor known for his work on U.S. history and for developing innovative role-immersion pedagogy in higher education.
  • D. Brian A. Kates
    Brian A. Kates is a film editor best known for his work on acclaimed independent and art-house films.
  • E. Michael T. Williamson
    Michael T. Williamson is an American actor best known for his role as Benjamin Buford "Bubba" Blue in the film Forrest Gump.
  • 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_69e0c457579481909db68053ed99750c completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9d04548819086594c20faa5217d completed April 23, 2026, 9:43 a.m.
Created at: April 16, 2026, 6:06 p.m.