Triple

T16063761
Position Surface form Disambiguated ID Type / Status
Subject Jan-Michael Vincent E389678 entity
Predicate notableWork P4 FINISHED
Object Red Line
Red Line is a 1996 American action film starring Jan-Michael Vincent, centered on illegal street racing and high-speed car chases.
E1196266 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: Red Line | Statement: [Jan-Michael Vincent, notableWork, Red Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Line
Context triple: [Jan-Michael Vincent, notableWork, Red Line]
  • A. Red Line
    The Red Line is a regional express bus route operated under the SolanoExpress system, providing intercity transit service in Solano County and surrounding areas.
  • B. Red Line
    The Red Line is one of the major corridors of the Delhi Metro rapid transit system, serving numerous densely populated areas in and around Delhi.
  • C. Red Line
    The Red Line is a primary route of the MetroLink light rail system serving key destinations in the St. Louis metropolitan area.
  • D. Red Line
    Red Line is one of the main rapid transit corridors of the Hyderabad Metro system in Hyderabad, India.
  • E. Red Line
    The Red Line is a light rail route in the Salt Lake City TRAX system that connects key destinations across the Salt Lake Valley.
  • 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: Red Line
Triple: [Jan-Michael Vincent, notableWork, Red Line]
Generated description
Red Line is a 1996 American action film starring Jan-Michael Vincent, centered on illegal street racing and high-speed car chases.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Red Line
Target entity description: Red Line is a 1996 American action film starring Jan-Michael Vincent, centered on illegal street racing and high-speed car chases.
  • A. Red Line
    Red Line is a major rapid transit route in the Washington Metro system, running through key areas of Washington, D.C., and its Maryland suburbs.
  • B. Red Line
    Red Line is a song by the American rock band Trans Am, known for their experimental blend of post-rock, electronic, and krautrock influences.
  • C. Red Line
    Red Line was the original name of Los Angeles Metro’s B Line, a heavy-rail subway corridor serving key neighborhoods between Downtown Los Angeles and North Hollywood.
  • D. Red Line
    The Red Line is a major rapid transit route in Chicago that runs north–south through the city, serving as one of the busiest lines in its subway and elevated rail system.
  • E. Red Line
    The Red Line is a major light rail route in the Dallas Area Rapid Transit (DART) system serving key corridors across the Dallas–Fort Worth metro area.
  • 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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837b048881908326739bbede756f completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff28f63c88190968ecbd4706b1331 completed May 10, 2026, 2:50 a.m.
NEDg Description generation batch_69fff35ded288190b4d261358f1661cb completed May 10, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69fff3f2760c8190a58fedc2798614ae completed May 10, 2026, 2:56 a.m.
Created at: April 10, 2026, 4:57 a.m.