Triple

T15711707
Position Surface form Disambiguated ID Type / Status
Subject Roger Yuan E380853 entity
Predicate notableWork P4 FINISHED
Object Redline
Redline is a 2007 American action film centered on high-stakes illegal street racing, exotic cars, and underground gambling.
 E1172437 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: Redline | Statement: [Roger Yuan, notableWork, Redline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Redline
Context triple: [Roger Yuan, notableWork, Redline]
  • A. White Line
    "White Line" is a grungy, guitar-driven rock song by Neil Young and Crazy Horse from the 1990 album *Ragged Glory*.
  • B. White Line
    White Line is one of the urban cable car routes in La Paz’s Mi Teleférico network, known for providing high-altitude public transit across the city.
  • C. Linha Vermelha
    Linha Vermelha is a major line of the Lisbon Metro system that connects key areas of the city, including the airport, to the broader urban rail network.
  • D. Röda linjen
    Röda linjen is one of the main lines of the Stockholm metro system, running in a north–south direction and serving several key suburbs and central city stations.
  • E. Down the Line
    Down the Line is a British radio comedy series presented as a spoof phone-in show, known for its improvised style and satirical take on talk radio.
  • 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: Redline
Triple: [Roger Yuan, notableWork, Redline]
Generated description
Redline is a 2007 American action film centered on high-stakes illegal street racing, exotic cars, and underground gambling.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Redline
Target entity description: Redline is a 2007 American action film centered on high-stakes illegal street racing, exotic cars, and underground gambling.
  • A. White Line
    White Line is one of the urban cable car routes in La Paz’s Mi Teleférico network, known for providing high-altitude public transit across the city.
  • B. White Line
    "White Line" is a grungy, guitar-driven rock song by Neil Young and Crazy Horse from the 1990 album *Ragged Glory*.
  • C. Linha Vermelha
    Linha Vermelha is a major line of the Lisbon Metro system that connects key areas of the city, including the airport, to the broader urban rail network.
  • D. Röda linjen
    Röda linjen is one of the main lines of the Stockholm metro system, running in a north–south direction and serving several key suburbs and central city stations.
  • E. Down the Line
    Down the Line is a British radio comedy series presented as a spoof phone-in show, known for its improvised style and satirical take on talk radio.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f8f5d6081908243fa59b46b7c76 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff757f571881908015fe68df2a5e69 completed May 9, 2026, 5:57 p.m.
NEDg Description generation batch_69ff769d305881908791ffcb0a30ee35 completed May 9, 2026, 6:02 p.m.
NED2 Entity disambiguation (via description) batch_69ff770b73d48190a422a0760c03f763 completed May 9, 2026, 6:03 p.m.
Created at: April 10, 2026, 4:45 a.m.