Triple

T2092373
Position Surface form Disambiguated ID Type / Status
Subject Robin Milner E32698 entity
Predicate givenName P17 FINISHED
Object John
John is the given first name of the influential British computer scientist Robin Milner, known for his pioneering work in programming language theory and process calculi.
E265391 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: [Robin Milner, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [Robin Milner, 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 the renowned British mathematician John H. Conway, known for his work in group theory, number theory, and the invention of the Game of Life.
  • D. 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.
  • 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: [Robin Milner, givenName, John]
Generated description
John is the given first name of the influential British computer scientist Robin Milner, known for his pioneering work in programming language theory and process calculi.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John is the given first name of the influential British computer scientist Robin Milner, known for his pioneering work in programming language theory and process calculi.
  • A. John
    John is the given name of John McCarthy, the American computer scientist who coined the term "artificial intelligence" and was a pioneer in the field.
  • B. John
    John is the given name of the renowned British mathematician John H. Conway, known for his work in group theory, number theory, and the invention of the Game of Life.
  • C. John
    John is the given name of John R. Pierce, an American engineer and scientist known for his pioneering work in communications and satellite technology.
  • D. John
    John is the given name of the influential English philosopher John Locke, a key figure in empiricism and liberal political theory.
  • E. John
    John is the given name of the British biochemist and crystallographer John Kendrew, a Nobel laureate known for determining the structure of myoglobin.
  • 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_69a885eba0708190999696a45cbec816 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba774ca881909f83cf65ffeb24bb completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebeee5a808190981c06b78d30f004 completed March 9, 2026, 12:37 p.m.
NEDg Description generation batch_69aec43352d88190a4e9ae4f315938db completed March 9, 2026, 12:59 p.m.
NED2 Entity disambiguation (via description) batch_69aec4adb21c8190a89d53588ad75438 completed March 9, 2026, 1:01 p.m.
Created at: March 4, 2026, 7:43 p.m.