Triple

T17772415
Position Surface form Disambiguated ID Type / Status
Subject John Russell, Viscount Amberley E443672 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John Russell, Viscount Amberley, a 19th-century British politician and the father of philosopher Bertrand Russell.
E104675 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: [John Russell, Viscount Amberley, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Russell, Viscount Amberley, givenName, John]
  • A. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • B. John
    John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
  • C. John
    John is the given first name of the 19th-century English theologian and social reformer Frederick Denison Maurice.
  • D. John
    John is the given name of John Eales, the renowned former Australian rugby union captain and World Cup winner.
  • E. John
    John is the given name of the English jurist and scholar John Selden, a prominent 17th-century authority on law and constitutional history.
  • 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: [John Russell, Viscount Amberley, givenName, John]
Generated description
John is the given name of John Russell, Viscount Amberley, a 19th-century British politician and the father of philosopher Bertrand Russell.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John Russell, Viscount Amberley, a 19th-century British politician and the father of philosopher Bertrand Russell.
  • A. John chosen
    John is the given name of John Russell, Viscount Amberley, a 19th-century British politician and the father of philosopher Bertrand Russell.
  • B. John
    John is the given name of John Russell, 1st Earl Russell, a prominent 19th-century British statesman and Prime Minister.
  • C. John
    John is the given name of John Russell, 4th Earl Russell, a British peer and politician.
  • D. John
    John is the given name of John Russell, 6th Duke of Bedford, a prominent British aristocrat and politician of the late 18th and early 19th centuries.
  • E. John
    John is the given name of 1st Viscount Simon, a prominent British Liberal politician and statesman of the early 20th century.
  • F. None of above.

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_69d8b9ef17708190bdf7e2adbf14ddc2 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4871a2130819081743ae89dddc64b completed April 19, 2026, 7:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a02efa7b3bc8190bfdb7bc4f3aa5371 completed May 12, 2026, 9:15 a.m.
NEDg Description generation batch_6a02f033da3081908124079eedc3a5c7 completed May 12, 2026, 9:17 a.m.
NED2 Entity disambiguation (via description) batch_6a02f103b3c8819097dda16ec3dfa84e completed May 12, 2026, 9:21 a.m.
Created at: April 10, 2026, 10:11 a.m.