Triple

T9614322
Position Surface form Disambiguated ID Type / Status
Subject Micron Technology E232180 entity
Predicate foundedBy P104 FINISHED
Object Ward Parkinson
Ward Parkinson is an American engineer and entrepreneur best known as a co-founder of the semiconductor company Micron Technology.
E811074 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: Ward Parkinson | Statement: [Micron Technology, foundedBy, Ward Parkinson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ward Parkinson
Context triple: [Micron Technology, foundedBy, Ward Parkinson]
  • A. Kenneth W. Parkinson
    Kenneth W. Parkinson is an American lawyer best known for being one of the defendants in the Watergate-related criminal case United States v. John N. Mitchell et al.
  • B. Roger Ward
    Roger Ward is an Australian actor best known for his role as the tough police officer Fifi Macaffee in the 1979 action film "Mad Max."
  • C. Richard Sibson
    Richard Sibson is a distinguished geologist recognized for his influential work on fault mechanics and earthquake processes.
  • D. David Wardle
    David Wardle is an illustrator and graphic designer known for creating book cover art, including the cover of Boris Johnson’s novel "Seventy-Two Virgins."
  • E. Ian Ward
    Ian Ward is a personal name shared by several notable individuals, including professionals in fields such as sports, academia, and the arts.
  • 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: Ward Parkinson
Triple: [Micron Technology, foundedBy, Ward Parkinson]
Generated description
Ward Parkinson is an American engineer and entrepreneur best known as a co-founder of the semiconductor company Micron Technology.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ward Parkinson
Target entity description: Ward Parkinson is an American engineer and entrepreneur best known as a co-founder of the semiconductor company Micron Technology.
  • A. Kenneth W. Parkinson
    Kenneth W. Parkinson is an American lawyer best known for being one of the defendants in the Watergate-related criminal case United States v. John N. Mitchell et al.
  • B. Roger Ward
    Roger Ward is an Australian actor best known for his role as the tough police officer Fifi Macaffee in the 1979 action film "Mad Max."
  • C. Richard Sibson
    Richard Sibson is a distinguished geologist recognized for his influential work on fault mechanics and earthquake processes.
  • D. David Wardle
    David Wardle is an illustrator and graphic designer known for creating book cover art, including the cover of Boris Johnson’s novel "Seventy-Two Virgins."
  • E. Ian Ward
    Ian Ward is a personal name shared by several notable individuals, including professionals in fields such as sports, academia, and the arts.
  • 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_69ca84867bb88190b4b57dd5a56d5691 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9aaaa47881908d69381d4d11f49b completed April 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69d17958287081908e337bdbe9ea366f completed April 4, 2026, 8:49 p.m.
NEDg Description generation batch_69d17d9d69908190879b160968e41745 completed April 4, 2026, 9:07 p.m.
NED2 Entity disambiguation (via description) batch_69d17e4c9e40819081367d2365bf5dd2 completed April 4, 2026, 9:10 p.m.
Created at: March 30, 2026, 8:09 p.m.