Triple

T4435977
Position Surface form Disambiguated ID Type / Status
Subject Sir John Colborne E95650 entity
Predicate givenName P17 FINISHED
Object John
John is the given name of Sir John Colborne, a British Army officer and colonial administrator who served as Lieutenant Governor of Upper Canada and later as Lord Seaton.
E438949 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: [Sir John Colborne, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [Sir John Colborne, givenName, John]
  • A. John
    John is the given name of John Hancock, a prominent American statesman and patriot best known for his large signature on the United States Declaration of Independence.
  • B. John
    John is the husband of Martha Rainsborough.
  • C. John
    John IV of Portugal was a 17th-century Portuguese king who restored the country's independence from Spain and founded the Braganza dynasty.
  • D. John
    John is the given name of John Henry Patterson, an American industrialist and founder of the National Cash Register Company.
  • E. John
    John is the first name of J. Michael Luttig, a prominent American conservative jurist and former federal appellate judge.
  • 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: [Sir John Colborne, givenName, John]
Generated description
John is the given name of Sir John Colborne, a British Army officer and colonial administrator who served as Lieutenant Governor of Upper Canada and later as Lord Seaton.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given name of Sir John Colborne, a British Army officer and colonial administrator who served as Lieutenant Governor of Upper Canada and later as Lord Seaton.
  • A. John
    John is the given name of Sir John Anderson, a British civil servant and politician who played a key role in government during the early 20th century.
  • B. John
    John is the given name of John Campbell, 4th Earl of Loudoun, a Scottish nobleman and British Army officer who served as commander-in-chief in North America during the early stages of the French and Indian War.
  • C. John
    John is the given name of John Rushworth Jellicoe, the British admiral who commanded the Grand Fleet at the Battle of Jutland and later served as First Sea Lord and Governor-General of New Zealand.
  • D. John
    John is the given name of Edward John Eyre, a 19th-century British explorer and colonial administrator known for his expeditions in Australia and controversial governorship in Jamaica.
  • E. John
    John is the given name of Lord Gort, a British Army officer and World War II field marshal.
  • 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_69b3453ea2b48190a26f154b3b8fece5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35589f8608190b0820d36beaacf44 completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6135ecdc08190b2a7458614cf4c54 completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b61464b0dc81909cab007115435b8b completed March 15, 2026, 2:07 a.m.
NED2 Entity disambiguation (via description) batch_69b6151440648190bf8c1c95e20caf13 completed March 15, 2026, 2:10 a.m.
Created at: March 12, 2026, 11:31 p.m.