Triple

T9341260
Position Surface form Disambiguated ID Type / Status
Subject Michael Crichton E224766 entity
Predicate directorOf P537 FINISHED
Object Coma
Coma is a 1978 medical thriller film, based on Robin Cook’s novel, that explores a sinister conspiracy involving patients mysteriously falling into comas in a Boston hospital.
E792709 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: Coma | Statement: [Michael Crichton, directorOf, Coma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coma
Context triple: [Michael Crichton, directorOf, Coma]
  • A. Coma
    "Coma" is a lengthy, hard rock track by Guns N' Roses known for its complex structure, dark themes, and climactic intensity.
  • B. Cooma
    Cooma is a town in New South Wales, Australia, known as a gateway to the Snowy Mountains and the Snowy Mountains Scheme.
  • C. Comas
    Comas is a populous urban district in northern Lima, Peru, known for its residential neighborhoods and commercial activity within the Greater Lima metropolitan area.
  • D. Coma Pedrosa
    Coma Pedrosa is the tallest mountain in Andorra, known for its rugged alpine terrain and popular hiking routes.
  • E. Biathanatos
    Biathanatos is a controversial prose work by John Donne that offers an unusual and paradoxical theological defense of suicide.
  • 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: Coma
Triple: [Michael Crichton, directorOf, Coma]
Generated description
Coma is a 1978 medical thriller film, based on Robin Cook’s novel, that explores a sinister conspiracy involving patients mysteriously falling into comas in a Boston hospital.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Coma
Target entity description: Coma is a 1978 medical thriller film, based on Robin Cook’s novel, that explores a sinister conspiracy involving patients mysteriously falling into comas in a Boston hospital.
  • A. Coma
    "Coma" is a lengthy, hard rock track by Guns N' Roses known for its complex structure, dark themes, and climactic intensity.
  • B. Cooma
    Cooma is a town in New South Wales, Australia, known as a gateway to the Snowy Mountains and the Snowy Mountains Scheme.
  • C. Comas
    Comas is a populous urban district in northern Lima, Peru, known for its residential neighborhoods and commercial activity within the Greater Lima metropolitan area.
  • D. Coma Pedrosa
    Coma Pedrosa is the tallest mountain in Andorra, known for its rugged alpine terrain and popular hiking routes.
  • E. Biathanatos
    Biathanatos is a controversial prose work by John Donne that offers an unusual and paradoxical theological defense of suicide.
  • 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_69ca84286fcc81909f6e7fd7a7e862a2 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd4bafa9108190889397614756020d completed April 1, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0e3f94ab88190a4c5a9129bd2ca14 completed April 4, 2026, 10:12 a.m.
NEDg Description generation batch_69d0e573af788190be4baaa3afb87ca2 completed April 4, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_69d0e607944c81909a421828595cd793 completed April 4, 2026, 10:20 a.m.
Created at: March 30, 2026, 7:40 p.m.