Triple

T10219991
Position Surface form Disambiguated ID Type / Status
Subject Craig Sager E242549 entity
Predicate fullName P16 FINISHED
Object Craig Graham Sager E242549 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: Craig Graham Sager | Statement: [Craig Sager, fullName, Craig Graham Sager]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Craig Graham Sager
Context triple: [Craig Sager, fullName, Craig Graham Sager]
  • A. Craig Sager chosen
    Craig Sager was a flamboyantly dressed and widely beloved American sports reporter best known for his colorful NBA sideline interviews and decades-long broadcasting career.
  • B. Amy Robach
    Amy Robach is an American television journalist and news anchor best known for her work on ABC’s “Good Morning America” and other major network news programs.
  • C. Brian Williams
    Brian Williams is an American television journalist best known for serving as the longtime anchor and managing editor of NBC Nightly News.
  • D. Michael Hastings
    Michael Hastings was a British playwright and screenwriter known for his stage and television works, including adaptations of notable literary and historical subjects.
  • E. Brian Thompson
    Brian Thompson is an American character actor known for his imposing physique and villainous roles in action films and television series.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa715a3c8190a9ccee7bcece0346 completed April 6, 2026, 12:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d6a82c98fc8190929b7b56f9a6e60d completed April 8, 2026, 7:10 p.m.
Created at: April 6, 2026, 11:08 a.m.