Triple

T11421825
Position Surface form Disambiguated ID Type / Status
Subject Ray Scapinello E270640 entity
Predicate nickname P55 FINISHED
Object Scamp
Scamp is the nickname of Ray Scapinello, a well-known former National Hockey League linesman recognized for his long and distinguished officiating career.
 E924539 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: Scamp | Statement: [Ray Scapinello, nickname, Scamp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Scamp
Context triple: [Ray Scapinello, nickname, Scamp]
  • A. Nibbler
    Nibbler is a small, seemingly cute but incredibly ancient and powerful alien creature from the animated series Futurama.
  • B. Roustabout
    Roustabout is a 1964 musical film starring Elvis Presley as a traveling carnival singer and motorcyclist.
  • C. Tobo
    Tobo is a small locality in eastern Sweden situated within Tierp Municipality in Uppsala County.
  • D. Peutie
    Peutie is a village in Flemish Brabant, Belgium, that forms a residential suburb of the nearby city of Vilvoorde.
  • E. Jip
    Jip is a central character in the British cult film "Human Traffic," known for his introspective narration and exploration of youth culture and clubbing in late-1990s Cardiff.
  • 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: Scamp
Triple: [Ray Scapinello, nickname, Scamp]
Generated description
Scamp is the nickname of Ray Scapinello, a well-known former National Hockey League linesman recognized for his long and distinguished officiating career.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Scamp
Target entity description: Scamp is the nickname of Ray Scapinello, a well-known former National Hockey League linesman recognized for his long and distinguished officiating career.
  • A. Nibbler
    Nibbler is a small, seemingly cute but incredibly ancient and powerful alien creature from the animated series Futurama.
  • B. Roustabout
    Roustabout is a 1964 musical film starring Elvis Presley as a traveling carnival singer and motorcyclist.
  • C. Tobo
    Tobo is a small locality in eastern Sweden situated within Tierp Municipality in Uppsala County.
  • D. Peutie
    Peutie is a village in Flemish Brabant, Belgium, that forms a residential suburb of the nearby city of Vilvoorde.
  • E. Jip
    Jip is a central character in the British cult film "Human Traffic," known for his introspective narration and exploration of youth culture and clubbing in late-1990s Cardiff.
  • 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_69d6aaddeaa8819088b30ef7b50598c9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d801b357e88190ace56d36a945688f completed April 9, 2026, 7:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5b8a1e88c8190994bea88a0490e60 completed April 20, 2026, 5:24 a.m.
NEDg Description generation batch_69e5c28d3824819097ff84cb4e13c923 completed April 20, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69e5c451c6c88190bcbb1f54ede35d29 completed April 20, 2026, 6:14 a.m.
Created at: April 8, 2026, 9:34 p.m.