Triple

T14841035
Position Surface form Disambiguated ID Type / Status
Subject John Van Buren E348963 entity
Predicate givenName P17 FINISHED
Object John
John is a 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 Van Buren, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Van Buren, 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 middle name of Samuel John Mills, an American Congregationalist minister known for his role in early 19th-century missionary movements.
  • C. John
    John is the given name of John C. Sheehan, an American organic chemist renowned for achieving the first complete laboratory synthesis of penicillin.
  • D. John
    John was a Portuguese royal who held the title of Prince of Brazil and later became King John VI of Portugal.
  • E. John
    John is the given name of John Boyle O'Reilly, a 19th-century Irish-born poet, journalist, and civil rights activist who became influential in the United States.
  • 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 Van Buren, givenName, John]
Generated description
John is a 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 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 the influential English philosopher John Locke, a key figure in empiricism and liberal political theory.
  • D. John
    John is the given name of John Adams, the second president of the United States and a prominent Founding Father.
  • E. John
    John is the given name of John Houseman, the Romanian-born British-American actor and producer known for his work in film, theater, and radio.
  • 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_69d822ec69008190a9232caa68836872 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded28e40f08190b309d8ac6404d2fc completed April 14, 2026, 11:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe389940e081908ad627955cb8d52e completed May 8, 2026, 7:25 p.m.
NEDg Description generation batch_69fe3a315d2c81908db44e7792908e39 completed May 8, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_69fe3bda81cc8190b256ec6284383dde completed May 8, 2026, 7:39 p.m.
Created at: April 10, 2026, 1:53 a.m.