Triple

T3269581
Position Surface form Disambiguated ID Type / Status
Subject John Dailey E68610 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 Dailey, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John Dailey, givenName, John]
  • A. John
    John is traditionally regarded as the author of the New Testament’s Book of Revelation, a prophetic and apocalyptic text in Christian scripture.
  • B. John
    John is the given name of John Perry Barlow, the American poet, essayist, and co-founder of the Electronic Frontier Foundation known for his advocacy of digital rights.
  • C. John
    John is the given name of John Nance Garner, who served as the 32nd vice president of the United States under President Franklin D. Roosevelt.
  • D. John
    John is the given first name of J. Michael Bishop, the American immunologist and Nobel Prize–winning scientist known for his work on oncogenes.
  • E. John
    John is the given name of John F. Sattler, likely referring to him in a more informal or abbreviated context.
  • 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 Dailey, 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 the given name of John Lennon, the iconic English singer-songwriter and co-founder of The Beatles.
  • 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 English actor and musician John Simm, known for roles in series such as "Life on Mars" and "Doctor Who."
  • E. John
    John is the given name of John Madden, the famed American football coach, broadcaster, and namesake of the Madden NFL video game series.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adafd0eddc8190834a64f6b8e8e9f9 completed March 8, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3bb50b48190a1d2ea0dd71c039f completed March 12, 2026, 5:11 p.m.
NEDg Description generation batch_69b2f9db711c8190a6903ae530ead9ea completed March 12, 2026, 5:37 p.m.
NED2 Entity disambiguation (via description) batch_69b312b273b48190a949e61b87722084 completed March 12, 2026, 7:23 p.m.
Created at: March 8, 2026, 3:09 p.m.