Triple

T19672336
Position Surface form Disambiguated ID Type / Status
Subject John Tayler E472362 entity
Predicate givenName P17 FINISHED
Object John
John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
E55602 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 Tayler, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Tayler, givenName, John]
  • A. John
    John is the given name of the prominent American architect John Russell Pope, known for designing monumental buildings in Washington, D.C.
  • B. John
    John is the given name of John J. Pershing, the famed American general who led the American Expeditionary Forces in World War I.
  • C. John
    John is the given first name of Johnny Kilbane, an American featherweight boxing champion from the early 20th century.
  • D. John
    John is the given name of John Albert William Spencer-Churchill, a British aristocrat and 10th Duke of Marlborough.
  • E. John
    John is the given name of John George Graves, a notable British mail-order entrepreneur and philanthropist from Sheffield.
  • 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 Tayler, givenName, John]
Generated description
John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is a common masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
  • A. John chosen
    John is a masculine given name of Hebrew origin, widely used in English-speaking countries and borne by numerous historical and contemporary figures.
  • B. John
    John is a common English surname borne by numerous individuals across various fields and cultures.
  • C. John
    John is the given name of John Graunt, a 17th-century English statistician and demographer known for pioneering work in population statistics.
  • D. John
    John is the given name of John Lennon, the iconic English singer-songwriter and co-founder of The Beatles.
  • E. John
    John is the given name of John Adams, the second president of the United States and a prominent Founding Father.
  • 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6416d61008190af531c6d346d7da1 completed April 20, 2026, 3:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07ab8822888190aac9a3df93b6fa64 completed May 15, 2026, 11:26 p.m.
NEDg Description generation batch_6a07ac20fb508190bcb9be8e46f9caa9 completed May 15, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_6a07ac8aa95c8190894b31ef9ebbf9ae completed May 15, 2026, 11:30 p.m.
Created at: April 10, 2026, 1:45 p.m.