Triple

T2289152
Position Surface form Disambiguated ID Type / Status
Subject Dirrty E51462 entity
Predicate writer P1360 FINISHED
Object John Colley
John Colley is a screenwriter best known for co-writing the film "Dirrty."
 E252679 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: John Colley | Statement: [Dirrty, writer, John Colley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Colley
Context triple: [Dirrty, writer, John Colley]
  • A. Andrew Barclay
    Andrew Barclay was an early American financier known for being among the original brokers who helped found what became the New York Stock Exchange.
  • B. Robert Barker
    Robert Barker was a 17th-century English royal printer best known for printing the first edition of the King James Bible.
  • C. Christopher Smyth
    Christopher Smyth was a 19th-century mountaineer known for making the first recorded ascent of Mont Blanc du Tacul in the Mont Blanc massif of the Alps.
  • D. Don Pedro Colley
    Don Pedro Colley was an American character actor best known for his roles in films and television series of the 1960s and 1970s, including science fiction and action genres.
  • E. John Blatchley
    John Blatchley was a British theatre director and educator best known as a co-founder of the influential Drama Centre London acting school.
  • 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: John Colley
Triple: [Dirrty, writer, John Colley]
Generated description
John Colley is a screenwriter best known for co-writing the film "Dirrty."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: John Colley
Target entity description: John Colley is a screenwriter best known for co-writing the film "Dirrty."
  • A. Andrew Barclay
    Andrew Barclay was an early American financier known for being among the original brokers who helped found what became the New York Stock Exchange.
  • B. Robert Barker
    Robert Barker was a 17th-century English royal printer best known for printing the first edition of the King James Bible.
  • C. Christopher Smyth
    Christopher Smyth was a 19th-century mountaineer known for making the first recorded ascent of Mont Blanc du Tacul in the Mont Blanc massif of the Alps.
  • D. Don Pedro Colley
    Don Pedro Colley was an American character actor best known for his roles in films and television series of the 1960s and 1970s, including science fiction and action genres.
  • E. John Blatchley
    John Blatchley was a British theatre director and educator best known as a co-founder of the influential Drama Centre London acting school.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc273b67c8190bcd96f9a484647ef completed March 7, 2026, 6:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae7f1e84ac819096cb62ce5e94d865 completed March 9, 2026, 8:04 a.m.
NEDg Description generation batch_69ae7fee12ac8190bb9924f7467434a6 completed March 9, 2026, 8:08 a.m.
NED2 Entity disambiguation (via description) batch_69ae8061cd348190b0b0b65dcf730f99 completed March 9, 2026, 8:10 a.m.
Created at: March 4, 2026, 7:48 p.m.