Triple

T280400
Position Surface form Disambiguated ID Type / Status
Subject Lester B. Pearson E5341 entity
Predicate givenName P17 FINISHED
Object Lester
Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
E49249 NE FINISHED

How this triple was built (4 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: Lester | Statement: [Lester B. Pearson, givenName, Lester]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lester
Context triple: [Lester B. Pearson, givenName, Lester]
  • A. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • B. Earl
    An Earl is a noble rank in the British and some European peerage systems, historically positioned below a marquess and above a viscount.
  • C. Walter
    Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
  • D. Gordon
    Gordon is the middle name of the famed Romantic poet Lord Byron, whose full name is George Gordon Byron.
  • E. Tom Canty
    Tom Canty is the impoverished London boy who swaps identities with Prince Edward in Mark Twain’s novel "The Prince and the Pauper," highlighting themes of class and social injustice.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lester
Triple: [Lester B. Pearson, givenName, Lester]
Generated description
Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lester
Target entity description: Lester is the given name of Lester B. Pearson, the Canadian diplomat, Nobel Peace Prize laureate, and 14th prime minister of Canada.
  • A. Leslie
    Leslie is a small town in Fife, Scotland, situated near Glenrothes and known historically for its textile and papermaking industries.
  • B. Earl
    An Earl is a noble rank in the British and some European peerage systems, historically positioned below a marquess and above a viscount.
  • C. Walter
    Walter is a masculine given name of Germanic origin that has been widely used in English-speaking countries.
  • D. Gordon
    Gordon is the middle name of the famed Romantic poet Lord Byron, whose full name is George Gordon Byron.
  • E. Henry Lucas
    Henry Lucas was a 17th-century English clergyman, politician, and benefactor whose endowment led to the creation of the prestigious Lucasian Chair of Mathematics at the University of Cambridge.
  • F. None of above. chosen

Provenance (5 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_69a257e6c8788190987dfe705ca2912a completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25e0868708190ad551ca06cc57f4a completed Feb. 28, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69a4034a3e248190853d58b4f27d1d74 completed March 1, 2026, 9:13 a.m.
NEDg Description generation batch_69a403e511888190a336cb34f4c3b960 completed March 1, 2026, 9:16 a.m.
NED2 Entity disambiguation (via description) batch_69a40451d2f881909b90d6d21c55c497 completed March 1, 2026, 9:18 a.m.
Created at: Feb. 28, 2026, 2:59 a.m.