Triple

T16249469
Position Surface form Disambiguated ID Type / Status
Subject Juno and the Paycock E394460 entity
Predicate stars P1956 FINISHED
Object Sidney Morgan
Sidney Morgan is an actor known for appearing in the film adaptation of Sean O'Casey’s play "Juno and the Paycock."
 E1202365 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: Sidney Morgan | Statement: [Juno and the Paycock, stars, Sidney Morgan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sidney Morgan
Context triple: [Juno and the Paycock, stars, Sidney Morgan]
  • A. Rita Morgan
    Rita Morgan is a fictional character from the television series "Dexter," known as Dexter Morgan's girlfriend and later wife whose tragic fate profoundly impacts the show's storyline.
  • B. Bessie
    Bessie is a feminine given name most famously associated with legendary American blues singer Bessie Smith.
  • C. Bessie
    Bessie is a character from "The Land of Dreams," likely serving as a central figure within its imaginative, dreamlike narrative world.
  • D. Bessie
    Bessie is the Third Doctor’s iconic vintage yellow roadster from Doctor Who, used as his primary mode of terrestrial transport.
  • E. Bessie
    Bessie is one of the central child protagonists in Enid Blyton’s classic fantasy series "The Magic Faraway Tree," known for her sensible and caring nature during the siblings’ adventures.
  • 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: Sidney Morgan
Triple: [Juno and the Paycock, stars, Sidney Morgan]
Generated description
Sidney Morgan is an actor known for appearing in the film adaptation of Sean O'Casey’s play "Juno and the Paycock."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sidney Morgan
Target entity description: Sidney Morgan is an actor known for appearing in the film adaptation of Sean O'Casey’s play "Juno and the Paycock."
  • A. Rita Morgan
    Rita Morgan is a fictional character from the television series "Dexter," known as Dexter Morgan's girlfriend and later wife whose tragic fate profoundly impacts the show's storyline.
  • B. Bessie
    Bessie is a feminine given name most famously associated with legendary American blues singer Bessie Smith.
  • C. Bessie
    Bessie is a character from "The Land of Dreams," likely serving as a central figure within its imaginative, dreamlike narrative world.
  • D. Bessie
    Bessie is the Third Doctor’s iconic vintage yellow roadster from Doctor Who, used as his primary mode of terrestrial transport.
  • E. Bessie
    Bessie is one of the central child protagonists in Enid Blyton’s classic fantasy series "The Magic Faraway Tree," known for her sensible and caring nature during the siblings’ adventures.
  • 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24594f23c8190bd59fcb2585cb5e3 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000ee568a48190835ce76f84461044 completed May 10, 2026, 4:51 a.m.
NEDg Description generation batch_6a0011995ff481908bbca9f9cfb41bf0 completed May 10, 2026, 5:03 a.m.
NED2 Entity disambiguation (via description) batch_6a0012669ff48190884367b92962a6d4 completed May 10, 2026, 5:06 a.m.
Created at: April 10, 2026, 5:04 a.m.