Triple

T9946160
Position Surface form Disambiguated ID Type / Status
Subject Kean E195208 entity
Predicate hasNotableBearer P458 FINISHED
Object William Kean
William Kean was an English stage and film actor active in the early 20th century, known for his character roles in British cinema and theatre.
 E837897 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: William Kean | Statement: [Kean, hasNotableBearer, William Kean]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: William Kean
Context triple: [Kean, hasNotableBearer, William Kean]
  • A. Daniel W. Carmichael
    Daniel W. Carmichael was a notable individual significant enough in his community or field to have a place or institution named in his honor.
  • B. John Ketcham
    John Ketcham is a film producer best known for his work on the biographical sports drama "The Hurricane."
  • C. James Honaker
    James Honaker is a political scientist and statistician known for his work on methods for handling missing data and for coauthoring influential research with Gary King.
  • D. Charles W. Scharf
    Charles W. Scharf is an American business executive and banking industry veteran who serves as the chief executive officer of Wells Fargo & Company.
  • E. George Keister
    George Keister was an American architect best known for designing prominent early 20th-century theaters and commercial buildings in New York City.
  • 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: William Kean
Triple: [Kean, hasNotableBearer, William Kean]
Generated description
William Kean was an English stage and film actor active in the early 20th century, known for his character roles in British cinema and theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: William Kean
Target entity description: William Kean was an English stage and film actor active in the early 20th century, known for his character roles in British cinema and theatre.
  • A. Daniel W. Carmichael
    Daniel W. Carmichael was a notable individual significant enough in his community or field to have a place or institution named in his honor.
  • B. John Ketcham
    John Ketcham is a film producer best known for his work on the biographical sports drama "The Hurricane."
  • C. James Honaker
    James Honaker is a political scientist and statistician known for his work on methods for handling missing data and for coauthoring influential research with Gary King.
  • D. Charles W. Scharf
    Charles W. Scharf is an American business executive and banking industry veteran who serves as the chief executive officer of Wells Fargo & Company.
  • E. George Keister
    George Keister was an American architect best known for designing prominent early 20th-century theaters and commercial buildings in New York City.
  • 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_69ca82e96a108190932bd1fc4acd73a0 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb655fba0819084a1e757b68c25d4 completed April 2, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69d281d5f6188190a7e657b1bd9bc607 completed April 5, 2026, 3:37 p.m.
NEDg Description generation batch_69d2860be32081909eec066c19552ba5 completed April 5, 2026, 3:55 p.m.
NED2 Entity disambiguation (via description) batch_69d2865c11c881909b6791bd2bf503c4 completed April 5, 2026, 3:57 p.m.
Created at: March 30, 2026, 8:45 p.m.