Triple

T13625156
Position Surface form Disambiguated ID Type / Status
Subject Andrew Barto E325558 entity
Predicate hasAcademicAdvisor P167 FINISHED
Object John Holland
John Holland was a pioneering American scientist known as the father of genetic algorithms and a key figure in the development of complex adaptive systems theory.
 E1051243 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 Holland | Statement: [Andrew Barto, hasAcademicAdvisor, John Holland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Holland
Context triple: [Andrew Barto, hasAcademicAdvisor, John Holland]
  • A. John Holland
    John Holland was an American actor known for his supporting roles in mid-20th-century film and television productions.
  • B. Michael Baker
    Michael Baker was a 19th-century American sea captain and explorer after whom the remote Pacific atoll Baker Island is named.
  • C. Bruce Smeaton
    Bruce Smeaton is an Australian composer best known for his film scores, particularly for notable Australian and international movies from the 1970s onward.
  • D. Walter P. Moore
    Walter P. Moore was a prominent American structural engineer known for pioneering work on large-span sports facilities and innovative stadium designs.
  • E. William Tracy
    William Tracy was an American film actor best known for his comedic roles in 1930s and 1940s Hollywood movies.
  • 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 Holland
Triple: [Andrew Barto, hasAcademicAdvisor, John Holland]
Generated description
John Holland was a pioneering American scientist known as the father of genetic algorithms and a key figure in the development of complex adaptive systems theory.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Holland
Target entity description: John Holland was a pioneering American scientist known as the father of genetic algorithms and a key figure in the development of complex adaptive systems theory.
  • A. John Holland
    John Holland was an American actor known for his supporting roles in mid-20th-century film and television productions.
  • B. Michael Baker
    Michael Baker was a 19th-century American sea captain and explorer after whom the remote Pacific atoll Baker Island is named.
  • C. Bruce Smeaton
    Bruce Smeaton is an Australian composer best known for his film scores, particularly for notable Australian and international movies from the 1970s onward.
  • D. Walter P. Moore
    Walter P. Moore was a prominent American structural engineer known for pioneering work on large-span sports facilities and innovative stadium designs.
  • E. William Tracy
    William Tracy was an American film actor best known for his comedic roles in 1930s and 1940s Hollywood movies.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbbe9c72c88190be3d7a3f2e96afbc completed April 12, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77fa4c5fc8190bd791f181fce2aa1 completed May 3, 2026, 5:02 p.m.
NEDg Description generation batch_69f78070e95c819088982e26fe2d8e26 completed May 3, 2026, 5:05 p.m.
NED2 Entity disambiguation (via description) batch_69f78157b9cc8190a1855cb9715aa7d5 completed May 3, 2026, 5:09 p.m.
Created at: April 9, 2026, 9:50 p.m.