Triple

T1531146
Position Surface form Disambiguated ID Type / Status
Subject Pearson E32445 entity
Predicate formerName P65 FINISHED
Object Pearson PLC 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 PLC | Statement: [Pearson, formerName, Pearson PLC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pearson PLC
Context triple: [Pearson, formerName, Pearson PLC]
  • A. Pearson chosen
    Pearson is a major British multinational publishing and education company known for its textbooks, assessments, and digital learning solutions worldwide.
  • B. Bertelsmann
    Bertelsmann is a major German multinational media, services, and education conglomerate known for owning prominent publishing and broadcasting companies worldwide.
  • C. Thomson Reuters
    Thomson Reuters is a multinational media and information services company best known for providing news, legal, financial, and business information to professionals worldwide.
  • D. Egmont Group
    Egmont Group is an international network of national financial intelligence units that collaborate to combat money laundering, terrorist financing, and other financial crimes.
  • E. Peel Group
    Peel Group is a major British infrastructure, transport, and real estate investment company known for owning and developing assets such as ports, airports, and large-scale property projects across the UK.
  • 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_69a885ea86308190998f6bc14bb91f8e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90816b5e88190aa92a8558e35744b completed March 5, 2026, 4:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad2957e6e4819087504a16bc32d60b completed March 8, 2026, 7:46 a.m.
Created at: March 4, 2026, 7:26 p.m.