Triple

T11981341
Position Surface form Disambiguated ID Type / Status
Subject John Bucyk E285166 entity
Predicate middleName P143 FINISHED
Object Paul
Paul is the middle name of Canadian former professional ice hockey player John Bucyk, a Hall of Fame left winger best known for his long career with the Boston Bruins.
E3700 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: Paul | Statement: [John Bucyk, middleName, Paul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul
Context triple: [John Bucyk, middleName, Paul]
  • A. Paul
    Paul is the middle-aged American widower portrayed by Marlon Brando in the controversial 1972 film "Last Tango in Paris."
  • B. Paul
    Paul is a laid-back, charming sperm donor whose unexpected involvement with his biological children disrupts a lesbian couple’s family dynamic in the film "The Kids Are All Right."
  • C. Paul
    Paul is a 2011 sci-fi comedy film about two British geeks who encounter a wisecracking alien during a road trip across the United States.
  • D. Paul
    Paul is a village and civil parish in Cornwall, England, known for its historic church and coastal setting near Penzance.
  • E. Paul
    Paul is a central character in the psychological horror film "It Comes at Night," portrayed as a protective family man struggling to safeguard his loved ones amid a mysterious, apocalyptic threat.
  • 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: Paul
Triple: [John Bucyk, middleName, Paul]
Generated description
Paul is the middle name of Canadian former professional ice hockey player John Bucyk, a Hall of Fame left winger best known for his long career with the Boston Bruins.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Paul
Target entity description: Paul is the middle name of Canadian former professional ice hockey player John Bucyk, a Hall of Fame left winger best known for his long career with the Boston Bruins.
  • A. Paul
    Paul is a family name most notably borne by Wolfgang Paul, the German physicist and Nobel laureate in Physics.
  • B. Paul chosen
    Paul is a masculine given name of Latin origin, widely used in many Western and Christian-influenced cultures.
  • C. Paul
    Paul is the middle-aged American widower portrayed by Marlon Brando in the controversial 1972 film "Last Tango in Paris."
  • D. Paul
    Paul is a central character in Terrence McNally’s play "The Lisbon Traviata," a darkly comic drama about friendship, obsession, and opera.
  • E. Paul
    Paul is a character from the "Wild" universe, known for his role within its adventurous, nature-centered narrative.
  • F. None of above.

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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90395a8788190bfbb3506c29e3825 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f4721913108190bd767c671f6484de completed May 1, 2026, 9:27 a.m.
NEDg Description generation batch_69f47b7ac4048190ae09f18f1a90338f completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47db91f38819092b7b5c5e2bb489b completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.