Triple

T1444294
Position Surface form Disambiguated ID Type / Status
Subject Wilkinson E31140 entity
Predicate hasNotableBearer P458 FINISHED
Object Michael Wilkinson
Michael Wilkinson is a British Labour Party politician who served as Member of Parliament for Ruislip-Northwood from 1997 to 2005.
 E258601 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: Michael Wilkinson | Statement: [Wilkinson, hasNotableBearer, Michael Wilkinson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael Wilkinson
Context triple: [Wilkinson, hasNotableBearer, Michael Wilkinson]
  • A. Ben Wilkinson
    Ben Wilkinson is a British poet, critic, and academic known for his contemporary poetry collections and contributions to literary journalism.
  • B. John Brett
    John Brett was a 19th-century British painter associated with the Pre-Raphaelite movement, renowned for his highly detailed landscapes and maritime scenes.
  • C. Paul Givan
    Paul Givan is a Democratic Unionist Party politician who served as First Minister of Northern Ireland.
  • D. John Leeson
    John Leeson is a British actor best known for voicing the robotic dog K-9 in the Doctor Who television franchise.
  • E. Andrew Whitham
    Andrew Whitham is a distinguished geoscientist recognized for his significant contributions to the field, as evidenced by his receipt of the William Smith Medal.
  • 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: Michael Wilkinson
Triple: [Wilkinson, hasNotableBearer, Michael Wilkinson]
Generated description
Michael Wilkinson is a British Labour Party politician who served as Member of Parliament for Ruislip-Northwood from 1997 to 2005.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael Wilkinson
Target entity description: Michael Wilkinson is a British Labour Party politician who served as Member of Parliament for Ruislip-Northwood from 1997 to 2005.
  • A. Ben Wilkinson
    Ben Wilkinson is a British poet, critic, and academic known for his contemporary poetry collections and contributions to literary journalism.
  • B. John Brett
    John Brett was a 19th-century British painter associated with the Pre-Raphaelite movement, renowned for his highly detailed landscapes and maritime scenes.
  • C. Paul Givan
    Paul Givan is a Democratic Unionist Party politician who served as First Minister of Northern Ireland.
  • D. John Leeson
    John Leeson is a British actor best known for voicing the robotic dog K-9 in the Doctor Who television franchise.
  • E. Andrew Whitham
    Andrew Whitham is a distinguished geoscientist recognized for his significant contributions to the field, as evidenced by his receipt of the William Smith Medal.
  • 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_69a4991633388190a4d61b5a98aa407a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c5353fdc819090481cbdd1162929 completed March 1, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae95d2a03881908433209da4af73a2 completed March 9, 2026, 9:41 a.m.
NEDg Description generation batch_69ae99a8058c8190a585171eaeffd1fd completed March 9, 2026, 9:58 a.m.
NED2 Entity disambiguation (via description) batch_69ae9a0c8638819086ebbe009672fd1d completed March 9, 2026, 9:59 a.m.
Created at: March 1, 2026, 8 p.m.