Triple

T4674000
Position Surface form Disambiguated ID Type / Status
Subject Nancy Goodman Brinker E103633 entity
Predicate hasSurname P18 FINISHED
Object Brinker E103633 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: Brinker | Statement: [Nancy Goodman Brinker, hasSurname, Brinker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brinker
Context triple: [Nancy Goodman Brinker, hasSurname, Brinker]
  • A. Brinker chosen
    Brinker is the surname of Nancy Goodman Brinker, the American businesswoman and philanthropist who founded the Susan G. Komen breast cancer organization.
  • B. Hillenbrand
    Hillenbrand is a surname of German origin borne by various notable individuals in fields such as diplomacy, literature, and sports.
  • C. Dunnigan
    Dunnigan is a small unincorporated community in Yolo County, California, known primarily as a rural agricultural area along Interstate 5.
  • D. Baker’s
    Baker’s is a regional American supermarket chain known for offering a full range of groceries and household goods.
  • E. Wahlburgers
    Wahlburgers is an American casual-dining burger restaurant and bar chain co-owned by the Wahlberg family and featured in a reality TV series of the same name.
  • 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_69bd43dda32c8190938b37744ca270fc completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd635326808190bd6909117aca1208 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be039896448190bdfd3a6cb76a8fbe completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:15 p.m.