Triple

T13334432
Position Surface form Disambiguated ID Type / Status
Subject Randall Pearson E317652 entity
Predicate familyName P18 FINISHED
Object Pearson E32445 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: Pearson | Statement: [Randall Pearson, familyName, Pearson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pearson
Context triple: [Randall Pearson, familyName, Pearson]
  • A. Pearson chosen
    Pearson is a major British multinational publishing and education company known for its textbooks, assessments, and digital learning solutions worldwide.
  • B. Prentice Hall
    Prentice Hall is a major American educational and professional publishing company known for its textbooks and academic titles across a wide range of disciplines.
  • C. McGraw-Hill
    McGraw-Hill is a major American educational publishing company known for producing textbooks and academic resources across a wide range of disciplines.
  • D. Cengage Learning
    Cengage Learning is a major educational content and technology company that produces textbooks, digital learning solutions, and course materials for higher education and professional markets worldwide.
  • E. Harcourt
    Harcourt is an English surname historically associated with a prominent aristocratic family involved in British politics and public life.
  • 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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99cff44e08190b9583baf0b626e42 completed April 11, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f730641f588190886119506e6dde8f completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:30 p.m.