Triple

T21846002
Position Surface form Disambiguated ID Type / Status
Subject Mr. Cheeks E539375 entity
Predicate notableWork P4 FINISHED
Object Lights, Camera, Action!
"Lights, Camera, Action!" is a hip hop single by rapper Mr. Cheeks, best known for its catchy party vibe and early-2000s club popularity.
 E1505079 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: Lights, Camera, Action! | Statement: [Mr. Cheeks, notableWork, Lights, Camera, Action!]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lights, Camera, Action!
Context triple: [Mr. Cheeks, notableWork, Lights, Camera, Action!]
  • A. Make a Movie
    Make a Movie is a special feature that guides viewers through the filmmaking process behind the creation of "The Perfect Storm."
  • B. REEL IT IN
    "REEL IT IN" is a popular hip-hop single by American rapper Aminé, known for its catchy hook and laid-back, bass-heavy production.
  • C. Show Time
    "Show Time" is a music album that follows Ry Cooder's "Chicken Skin Music" in his discography.
  • D. Reel Time
    Reel Time is a Philippine documentary television program known for its in-depth, human-interest stories and social issue features.
  • E. Making Movies
    Making Movies is a 1980 rock album by Dire Straits known for its cinematic songwriting and tracks like "Romeo and Juliet" and "Tunnel of Love."
  • 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: Lights, Camera, Action!
Triple: [Mr. Cheeks, notableWork, Lights, Camera, Action!]
Generated description
"Lights, Camera, Action!" is a hip hop single by rapper Mr. Cheeks, best known for its catchy party vibe and early-2000s club popularity.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lights, Camera, Action!
Target entity description: "Lights, Camera, Action!" is a hip hop single by rapper Mr. Cheeks, best known for its catchy party vibe and early-2000s club popularity.
  • A. Make a Movie
    Make a Movie is a special feature that guides viewers through the filmmaking process behind the creation of "The Perfect Storm."
  • B. REEL IT IN
    "REEL IT IN" is a popular hip-hop single by American rapper Aminé, known for its catchy hook and laid-back, bass-heavy production.
  • C. Show Time
    "Show Time" is a music album that follows Ry Cooder's "Chicken Skin Music" in his discography.
  • D. Reel Time
    Reel Time is a Philippine documentary television program known for its in-depth, human-interest stories and social issue features.
  • E. Making Movies
    Making Movies is a 1980 rock album by Dire Straits known for its cinematic songwriting and tracks like "Romeo and Juliet" and "Tunnel of Love."
  • 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_69e0c476c3c88190a92d08ebb59a128a completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f0bd546fb48190a7b815233650c2e7 completed April 28, 2026, 1:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a4bcabfdc819083ffb78747a50a82 completed May 17, 2026, 11:14 p.m.
NEDg Description generation batch_6a0a4ceefdd88190aa3790bfd9df882b completed May 17, 2026, 11:19 p.m.
NED2 Entity disambiguation (via description) batch_6a0a4da50c988190a41a4fcb83ae02a6 completed May 17, 2026, 11:22 p.m.
Created at: April 16, 2026, 6:55 p.m.