Triple

T7561267
Position Surface form Disambiguated ID Type / Status
Subject Non-Stop E178798 entity
Predicate character P662 FINISHED
Object Bill Marks
Bill Marks is the troubled yet determined U.S. federal air marshal portrayed by Liam Neeson in the action-thriller film "Non-Stop."
 E677621 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: Bill Marks | Statement: [Non-Stop, character, Bill Marks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bill Marks
Context triple: [Non-Stop, character, Bill Marks]
  • A. Dennis Marks
    Dennis Marks is a name shared by several notable individuals, including an American television producer and writer and a British opera director and translator.
  • B. David Marks
    David Marks was a British architect best known as the co-designer of the London Eye and other major public structures.
  • C. David Marks
    David Marks is an American guitarist and singer best known as an early member of the iconic rock band The Beach Boys.
  • D. J.B. Marks
    J.B. Marks was a South African communist leader and anti-apartheid activist who played a significant role in resistance politics during the mid-20th century.
  • E. Sean Marks
    Sean Marks is a former NBA player and basketball executive best known for serving as the general manager who led the Brooklyn Nets’ roster rebuild in the late 2010s.
  • 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: Bill Marks
Triple: [Non-Stop, character, Bill Marks]
Generated description
Bill Marks is the troubled yet determined U.S. federal air marshal portrayed by Liam Neeson in the action-thriller film "Non-Stop."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bill Marks
Target entity description: Bill Marks is the troubled yet determined U.S. federal air marshal portrayed by Liam Neeson in the action-thriller film "Non-Stop."
  • A. Dennis Marks
    Dennis Marks is a name shared by several notable individuals, including an American television producer and writer and a British opera director and translator.
  • B. David Marks
    David Marks was a British architect best known as the co-designer of the London Eye and other major public structures.
  • C. David Marks
    David Marks is an American guitarist and singer best known as an early member of the iconic rock band The Beach Boys.
  • D. J.B. Marks
    J.B. Marks was a South African communist leader and anti-apartheid activist who played a significant role in resistance politics during the mid-20th century.
  • E. Sean Marks
    Sean Marks is a former NBA player and basketball executive best known for serving as the general manager who led the Brooklyn Nets’ roster rebuild in the late 2010s.
  • 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_69c69f2f80288190b95cceb4da92ab2b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8f847c48190a1081aa9de7ff945 completed March 27, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c870780d24819095196cd3a22bec5a completed March 29, 2026, 12:21 a.m.
NEDg Description generation batch_69c8725e42a481909bf442987fca3a8c completed March 29, 2026, 12:29 a.m.
NED2 Entity disambiguation (via description) batch_69c872f89ff08190809d476ae6809488 completed March 29, 2026, 12:31 a.m.
Created at: March 27, 2026, 3:50 p.m.