Triple

T3599984
Position Surface form Disambiguated ID Type / Status
Subject John W. Tukey E76231 entity
Predicate givenName P17 FINISHED
Object John
John W. Tukey was an influential American mathematician and statistician known for pioneering exploratory data analysis and coining the term "bit."
E373429 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 W. Tukey, givenName, John]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John
Context triple: [John W. Tukey, givenName, John]
  • A. John
    John H. Sununu is an American politician and engineer who served as Governor of New Hampshire and later as White House Chief of Staff under President George H. W. Bush.
  • B. John
    John is traditionally regarded as the author of the New Testament’s Book of Revelation, a prophetic and apocalyptic text in Christian scripture.
  • C. John
    John is the given name of John F. Sattler, likely referring to him in a more informal or abbreviated context.
  • D. John
    John is the given name of John L. Lewis, the influential American labor leader who headed the United Mine Workers of America and helped shape the modern labor movement.
  • E. John
    John is the given name of John Dryden Kuser, an American politician and member of a prominent New Jersey family in the early 20th century.
  • 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 W. Tukey, givenName, John]
Generated description
John W. Tukey was an influential American mathematician and statistician known for pioneering exploratory data analysis and coining the term "bit."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: John
Target entity description: John W. Tukey was an influential American mathematician and statistician known for pioneering exploratory data analysis and coining the term "bit."
  • A. John
    John is the given name of the American mathematician John Tate, renowned for his foundational contributions to number theory and arithmetic geometry.
  • B. John
    John is the given name of John W. Mauchly, the American physicist and co-inventor of the ENIAC computer.
  • 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 John McCarthy, the American computer scientist who coined the term "artificial intelligence" and was a pioneer in the field.
  • E. John
    John is the given first name of J. Presper Eckert, the American electrical engineer and co-inventor of the ENIAC computer.
  • 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_69ad85d93dcc819094fba90cf70f4996 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc19fd57481908ce5c9daf168e213 completed March 8, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69b432ffc2f4819099b340be8c6b5bb6 completed March 13, 2026, 3:53 p.m.
NEDg Description generation batch_69b43757dd1481909bce2fe5b57234eb completed March 13, 2026, 4:12 p.m.
NED2 Entity disambiguation (via description) batch_69b437e30620819098f7a9e7fe33d4cd completed March 13, 2026, 4:14 p.m.
Created at: March 8, 2026, 3:22 p.m.