Triple

T362014
Position Surface form Disambiguated ID Type / Status
Subject Koop E7875 entity
Predicate hasNotableBearer P458 FINISHED
Object Stanley Koop
Stanley Koop is an individual notable enough to be recognized as a prominent bearer of the surname Koop.
 E67628 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: Stanley Koop | Statement: [Koop, hasNotableBearer, Stanley Koop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Stanley Koop
Context triple: [Koop, hasNotableBearer, Stanley Koop]
  • A. Henry Koster
    Henry Koster was a German-born American film director best known for his work in Hollywood during the 1930s–1950s, including popular comedies, dramas, and family films.
  • B. George Boemler
    George Boemler was a film editor known for his work on classic Hollywood productions, including the musical comedy "High Society."
  • C. Tony Koop
    Tony Koop is an individual notable enough to be recognized as a namesake of the surname Koop, though specific widely known public details about him are limited.
  • D. Don Brochu
    Don Brochu is a film editor best known for his work on major Hollywood movies, including the hit thriller "The Bodyguard."
  • E. Joseph Buloff
    Joseph Buloff was a Lithuanian-born American actor and director known for his work in Yiddish theater and on Broadway.
  • 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: Stanley Koop
Triple: [Koop, hasNotableBearer, Stanley Koop]
Generated description
Stanley Koop is an individual notable enough to be recognized as a prominent bearer of the surname Koop.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Stanley Koop
Target entity description: Stanley Koop is an individual notable enough to be recognized as a prominent bearer of the surname Koop.
  • A. Henry Koster
    Henry Koster was a German-born American film director best known for his work in Hollywood during the 1930s–1950s, including popular comedies, dramas, and family films.
  • B. George Boemler
    George Boemler was a film editor known for his work on classic Hollywood productions, including the musical comedy "High Society."
  • C. Tony Koop
    Tony Koop is an individual notable enough to be recognized as a namesake of the surname Koop, though specific widely known public details about him are limited.
  • D. Don Brochu
    Don Brochu is a film editor best known for his work on major Hollywood movies, including the hit thriller "The Bodyguard."
  • E. Joseph Buloff
    Joseph Buloff was a Lithuanian-born American actor and director known for his work in Yiddish theater and on Broadway.
  • 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_69a2e7e880008190a6ad7e06e5d03007 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ebce64c88190a0a8edcc7095f78b completed Feb. 28, 2026, 1:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4cc562bc08190b5f1a6f143bd13d1 completed March 1, 2026, 11:31 p.m.
NEDg Description generation batch_69a4cd4fdd048190a0717e884a2a0d6d completed March 1, 2026, 11:35 p.m.
NED2 Entity disambiguation (via description) batch_69a4cdb9bc44819086cff5102a0ce7fd completed March 1, 2026, 11:37 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.