Triple

T15198157
Position Surface form Disambiguated ID Type / Status
Subject John William Friso, Prince of Orange E363192 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of John William Friso, a Dutch nobleman who served as Prince of Orange and stadtholder in the early 18th century.
E1142836 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 William Friso, Prince of Orange, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John William Friso, Prince of Orange, 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 Sir John Lennard-Jones, a pioneering British theoretical chemist known for his work on intermolecular forces and the Lennard-Jones potential.
  • 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 William Friso, Prince of Orange, givenName, John]
Generated description
John is the given name of John William Friso, a Dutch nobleman who served as Prince of Orange and stadtholder in the early 18th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of John William Friso, a Dutch nobleman who served as Prince of Orange and stadtholder in the early 18th century.
  • A. John
    John is the given name of John Churchill, 1st Duke of Marlborough, the renowned English general and statesman of the late 17th and early 18th centuries.
  • B. 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.
  • C. John
    John is the given name of John Murray, 3rd Duke of Atholl, an 18th-century Scottish nobleman and peer.
  • D. John
    John is the given name of John Campbell, 2nd Duke of Argyll, a prominent Scottish nobleman and military leader of the early 18th century.
  • E. John
    John is the given name of John Campbell, 5th Duke of Argyll, a prominent 18th-century Scottish nobleman and military leader.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006b476208190a5119710c518bb1f completed April 15, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed3304464819083732a23e650c649 completed May 9, 2026, 6:24 a.m.
NEDg Description generation batch_69fed46caba481908864d62936659a6d completed May 9, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_69fed4f5be0c8190a1fb6e1a176c5208 completed May 9, 2026, 6:32 a.m.
Created at: April 10, 2026, 3:10 a.m.