Triple

T497736
Position Surface form Disambiguated ID Type / Status
Subject Martha Rogers E10331 entity
Predicate name P16 FINISHED
Object Martha Rogers E10331 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: Martha Rogers | Statement: [Martha Rogers, name, Martha Rogers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martha Rogers
Context triple: [Martha Rogers, name, Martha Rogers]
  • A. Martha Rogers chosen
    Martha Rogers is a member of the prominent Rogers family of Canadian business and telecommunications, known as a daughter of the late media magnate Ted Rogers.
  • B. Florence Nightingale Graham
    Florence Nightingale Graham, better known as Elizabeth Arden, was a pioneering Canadian-American businesswoman who built a global cosmetics empire and helped shape the modern beauty industry.
  • C. Jane Belson
    Jane Belson was a British barrister best known as the wife of author Douglas Adams.
  • D. Nancy Packard Burnett
    Nancy Packard Burnett is an American philanthropist and member of the Packard family who has supported environmental, educational, and cultural initiatives.
  • E. Dolores H. Russ
    Dolores H. Russ was an American philanthropist and co-namesake of the prestigious Fritz J. and Dolores H. Russ Prize in engineering.
  • 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_69a2e847df8481909239ec08ccf1e376 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1183e988190bce70932a9678134 completed Feb. 28, 2026, 1:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a481efc3a881909575c5981e13a16b completed March 1, 2026, 6:14 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.