Triple

T16927374
Position Surface form Disambiguated ID Type / Status
Subject Baupost Group E410610 entity
Predicate founder P104 FINISHED
Object Howard Stevenson
Howard Stevenson is an American entrepreneur, educator, and longtime Harvard Business School professor known for his influential work on entrepreneurship and venture capital.
E1283540 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: Howard Stevenson | Statement: [Baupost Group, founder, Howard Stevenson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard Stevenson
Context triple: [Baupost Group, founder, Howard Stevenson]
  • A. Tim Stevenson
    Tim Stevenson is a British public servant who has served as the ceremonial representative of the monarch in Oxfordshire.
  • B. Gary Stevenson
    Gary Stevenson is the husband of the late American author and social critic Barbara Ehrenreich.
  • C. John Stevenson
    John Stevenson is an alternative name used for John Stephenson, who may be referenced under either spelling in various records or contexts.
  • D. David Stevenson
    David Stevenson was a Scottish lighthouse engineer and member of the famous Stevenson family of civil engineers.
  • E. Michael Steadman
    Michael Steadman is a central character on the television drama "thirtysomething," portrayed as a sensitive, idealistic young professional navigating marriage, career, and adulthood in the late 1980s.
  • 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: Howard Stevenson
Triple: [Baupost Group, founder, Howard Stevenson]
Generated description
Howard Stevenson is an American entrepreneur, educator, and longtime Harvard Business School professor known for his influential work on entrepreneurship and venture capital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Howard Stevenson
Target entity description: Howard Stevenson is an American entrepreneur, educator, and longtime Harvard Business School professor known for his influential work on entrepreneurship and venture capital.
  • A. Tim Stevenson
    Tim Stevenson is a British public servant who has served as the ceremonial representative of the monarch in Oxfordshire.
  • B. Gary Stevenson
    Gary Stevenson is the husband of the late American author and social critic Barbara Ehrenreich.
  • C. John Stevenson
    John Stevenson is an alternative name used for John Stephenson, who may be referenced under either spelling in various records or contexts.
  • D. David Stevenson
    David Stevenson was a Scottish lighthouse engineer and member of the famous Stevenson family of civil engineers.
  • E. Michael Steadman
    Michael Steadman is a central character on the television drama "thirtysomething," portrayed as a sensitive, idealistic young professional navigating marriage, career, and adulthood in the late 1980s.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cdf3fc3c8190a884f7ecd5c47adb completed April 18, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a023007da0c81908a9665d62a24b44c completed May 11, 2026, 7:37 p.m.
NEDg Description generation batch_6a023192ea9c819096bf6ed8952f21c4 completed May 11, 2026, 7:44 p.m.
NED2 Entity disambiguation (via description) batch_6a02321a9c6c8190a86ebfdcfa32f786 completed May 11, 2026, 7:46 p.m.
Created at: April 10, 2026, 5:30 a.m.