Triple

T23091208
Position Surface form Disambiguated ID Type / Status
Subject John Hugh McNary E575753 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 Hugh McNary, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Hugh McNary, givenName, John]
  • A. John
    John is the nickname of John Riggins, a former American football running back best known for his Hall of Fame career with the Washington Redskins in the NFL.
  • B. John
    John is the given name of the American composer John Luther Adams, known for his works inspired by nature and environmental themes.
  • C. John
    John is the first name of John Dashwood, a character in Jane Austen's novel "Sense and Sensibility."
  • D. John
    John is the given first name of American character actor and comedian Rags Ragland.
  • E. John
    John is the first name of the fictional character John Connor, the prophesied leader of the human resistance in the Terminator franchise.
  • 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 Hugh McNary, 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_69e245bf3e3c819086d3448720efc01b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18daa68d48190842e9cb6de31ea79 completed April 29, 2026, 4:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c159ffb7481909b2987e8aea047ca completed May 19, 2026, 7:47 a.m.
NEDg Description generation batch_6a0c17214dc48190be02f8d83c29b90a completed May 19, 2026, 7:54 a.m.
NED2 Entity disambiguation (via description) batch_6a0c17da6a108190b37d1e69e6f24e00 completed May 19, 2026, 7:57 a.m.
Created at: April 17, 2026, 3:57 p.m.