Triple

T12862468
Position Surface form Disambiguated ID Type / Status
Subject Elisabeth Hasselbeck E307627 entity
Predicate relative P37 FINISHED
Object Matt Hasselbeck E193533 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: Matt Hasselbeck | Statement: [Elisabeth Hasselbeck, relative, Matt Hasselbeck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Hasselbeck
Context triple: [Elisabeth Hasselbeck, relative, Matt Hasselbeck]
  • A. Matt Hasselbeck chosen
    Matt Hasselbeck is a former NFL quarterback best known for leading the Seattle Seahawks to multiple playoff appearances and a Super Bowl berth in the 2000s.
  • B. Tim Hasselbeck
    Tim Hasselbeck is a former NFL quarterback who later became a football analyst and commentator for ESPN.
  • C. Don Hasselbeck
    Don Hasselbeck is a former American football tight end who played in the NFL, notably for the New England Patriots, during the late 1970s and early 1980s.
  • D. Sarah Hasselbeck
    Sarah Hasselbeck is known as the wife of former NFL quarterback and sports analyst Matt Hasselbeck.
  • E. Brian Griese
    Brian Griese is a former American NFL quarterback who played primarily for the Denver Broncos and later became a football analyst and coach.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9708ba74881909b16c1e2ef5115db completed April 10, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af533d188190b9c816cdc892fe99 completed May 3, 2026, 2:13 a.m.
Created at: April 9, 2026, 5:37 p.m.