Triple

T14818502
Position Surface form Disambiguated ID Type / Status
Subject Lord John Townshend E348381 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of Lord John Townshend, an 18th–19th century British Whig politician and member of the influential Townshend family.
E1121541 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: John | Statement: [Lord John Townshend, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [Lord John Townshend, givenName, John]
  • A. John
    John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
  • B. John
    John is the given name of John Reith, the influential first Director-General of the BBC who shaped early public service broadcasting in the United Kingdom.
  • C. John
    John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
  • D. John
    John is the given first name of American character actor and comedian Rags Ragland.
  • E. John
    John is the given name of actor John Cho, a Korean American performer known for roles in the "Harold & Kumar" films and the "Star Trek" reboot series.
  • 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: John
Triple: [Lord John Townshend, givenName, John]
Generated description
John is the given name of Lord John Townshend, an 18th–19th century British Whig politician and member of the influential Townshend family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of Lord John Townshend, an 18th–19th century British Whig politician and member of the influential Townshend family.
  • A. John
    John is the given name of Lord John Manners, a 19th-century British Conservative politician and member of the aristocratic Manners family.
  • B. John
    John is the given name of Lord Palmerston, the 19th-century British statesman who served twice as Prime Minister of the United Kingdom.
  • C. John
    John is the given name of John Wodehouse, 1st Earl of Kimberley, a prominent 19th-century British Liberal politician and statesman.
  • D. John
    John is the given name of John Churchill, Marquess of Blandford, an English nobleman from the prominent Churchill family in the early 18th century.
  • E. John
    John is the given name of John Copley, 1st Baron Lyndhurst, a prominent 19th-century British lawyer and Conservative politician who served three times as Lord Chancellor.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe4cf38819090f25ef045351d5d completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe389940e081908ad627955cb8d52e completed May 8, 2026, 7:25 p.m.
NEDg Description generation batch_69fe3a315d2c81908db44e7792908e39 completed May 8, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_69fe3bda81cc8190b256ec6284383dde completed May 8, 2026, 7:39 p.m.
Created at: April 10, 2026, 1:50 a.m.