Triple

T12754376
Position Surface form Disambiguated ID Type / Status
Subject John de la Pole E304818 entity
Predicate givenName P17 FINISHED
Object John
John de la Pole was a 15th-century English nobleman and Yorkist claimant to the English throne during the Wars of the Roses.
E1004880 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 de la Pole, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John de la Pole, givenName, John]
  • A. John
    John Vassall Jr. was a British civil servant who became notorious as a Soviet spy during the Cold War.
  • B. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • C. John
    John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
  • D. John
    John is the middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
  • E. John
    John Ross is a personal name shared by various notable individuals across history, including leaders, politicians, and public figures.
  • 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 de la Pole, givenName, John]
Generated description
John de la Pole was a 15th-century English nobleman and Yorkist claimant to the English throne during the Wars of the Roses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John de la Pole was a 15th-century English nobleman and Yorkist claimant to the English throne during the Wars of the Roses.
  • A. John
    John, Prince of Lancaster, was a 15th-century English royal and military commander, best known for his role in the Hundred Years' War and as the younger son of King Henry IV.
  • B. John
    John is the given name of Sir John Woodville, a 15th-century English nobleman associated with the influential Woodville family during the Wars of the Roses.
  • C. John
    John the Fearless was a powerful early 15th-century Duke of Burgundy known for his aggressive political maneuvers and pivotal role in the French civil conflicts of the Hundred Years’ War.
  • D. John
    John V, Duke of Brittany, was a 15th-century French nobleman who ruled the Duchy of Brittany and played a significant role in the politics of the Hundred Years' War.
  • E. John
    John Beaufort, 1st Earl of Somerset, was an English nobleman and military commander, the eldest of John of Gaunt’s legitimized Beaufort children and a prominent figure in the early Lancastrian dynasty.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96d89ea70819098c470344f172167 completed April 10, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68eb388488190a30866e9a7a0bc41 completed May 2, 2026, 11:54 p.m.
NEDg Description generation batch_69f68fb6790881908c1d6f53b54906a2 completed May 2, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_69f690c0bd208190bd1f04a9640ad1ce completed May 3, 2026, 12:03 a.m.
Created at: April 9, 2026, 5:27 p.m.