Triple

T1694285
Position Surface form Disambiguated ID Type / Status
Subject Effie Gray E36620 entity
Predicate composer P1361 FINISHED
Object Paul Cantelon
Paul Cantelon is an American composer and multi-instrumentalist known for his film scores and work blending classical, jazz, and world music influences.
 E237027 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 Cantelon | Statement: [Effie Gray, composer, Paul Cantelon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paul Cantelon
Context triple: [Effie Gray, composer, Paul Cantelon]
  • A. Andrew Carnes
    Andrew Carnes is a character in the musical "Oklahoma!", known as the protective father of Ado Annie.
  • B. Chris Klein
    Chris Klein is a former American professional soccer player who later became a sports executive, notably serving as president of Major League Soccer’s LA Galaxy.
  • C. Joel Stransky
    Joel Stransky is a former South African rugby union fly-half best known for kicking the winning drop goal in the 1995 Rugby World Cup final.
  • D. Colin Kroll
    Colin Kroll was an American technology entrepreneur best known as the co-founder of the short-form video platform Vine and the mobile trivia game HQ Trivia.
  • E. Michael Cerenzie
    Michael Cerenzie is a film producer known for his work on independent and genre films in Hollywood.
  • 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 Cantelon
Triple: [Effie Gray, composer, Paul Cantelon]
Generated description
Paul Cantelon is an American composer and multi-instrumentalist known for his film scores and work blending classical, jazz, and world music influences.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paul Cantelon
Target entity description: Paul Cantelon is an American composer and multi-instrumentalist known for his film scores and work blending classical, jazz, and world music influences.
  • A. Andrew Carnes
    Andrew Carnes is a character in the musical "Oklahoma!", known as the protective father of Ado Annie.
  • B. Chris Klein
    Chris Klein is a former American professional soccer player who later became a sports executive, notably serving as president of Major League Soccer’s LA Galaxy.
  • C. Joel Stransky
    Joel Stransky is a former South African rugby union fly-half best known for kicking the winning drop goal in the 1995 Rugby World Cup final.
  • D. Colin Kroll
    Colin Kroll was an American technology entrepreneur best known as the co-founder of the short-form video platform Vine and the mobile trivia game HQ Trivia.
  • E. Michael Cerenzie
    Michael Cerenzie is a film producer known for his work on independent and genre films in Hollywood.
  • 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_69a886163dec8190859c514232a37a05 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa62b3b8908190afc3f9e4a384684f completed March 6, 2026, 5:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae516742dc81909915c49b12645c26 completed March 9, 2026, 4:49 a.m.
NEDg Description generation batch_69ae524946f881908452e7f414962e70 completed March 9, 2026, 4:53 a.m.
NED2 Entity disambiguation (via description) batch_69ae529f2e508190b7483b70c9dbf9f9 completed March 9, 2026, 4:54 a.m.
Created at: March 4, 2026, 7:29 p.m.