Triple

T15653011
Position Surface form Disambiguated ID Type / Status
Subject Bounty Killer E376358 entity
Predicate notableWork P4 FINISHED
Object Look
"Look" is a dancehall track by Jamaican deejay Bounty Killer, recognized as one of his popular songs within the genre.
 E1169492 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: Look | Statement: [Bounty Killer, notableWork, Look]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Look
Context triple: [Bounty Killer, notableWork, Look]
  • A. Look
    "Look" is a critically acclaimed album by American musician and producer Blake Mills, noted for its experimental guitar work and innovative soundscapes.
  • B. Look
    Look is a French cycling brand best known for pioneering clipless pedals and innovative carbon fiber bicycle frames used by professional racing teams.
  • C. Looks
    "Looks" is a young adult novel by Madeleine George that explores themes of body image, bullying, and friendship through the intersecting lives of two marginalized high school girls.
  • D. the look
    The look is Jean-Paul Sartre’s existentialist concept describing how becoming aware of another’s gaze reveals our own objectification and shapes our sense of self.
  • E. Looking
    Looking is an HBO comedy-drama television series that follows the lives and relationships of a group of gay friends living in San Francisco.
  • 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: Look
Triple: [Bounty Killer, notableWork, Look]
Generated description
"Look" is a dancehall track by Jamaican deejay Bounty Killer, recognized as one of his popular songs within the genre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Look
Target entity description: "Look" is a dancehall track by Jamaican deejay Bounty Killer, recognized as one of his popular songs within the genre.
  • A. Look
    "Look" is a critically acclaimed album by American musician and producer Blake Mills, noted for its experimental guitar work and innovative soundscapes.
  • B. Look
    Look is a French cycling brand best known for pioneering clipless pedals and innovative carbon fiber bicycle frames used by professional racing teams.
  • C. Looks
    "Looks" is a young adult novel by Madeleine George that explores themes of body image, bullying, and friendship through the intersecting lives of two marginalized high school girls.
  • D. the look
    The look is Jean-Paul Sartre’s existentialist concept describing how becoming aware of another’s gaze reveals our own objectification and shapes our sense of self.
  • E. Looking
    Looking is an HBO comedy-drama television series that follows the lives and relationships of a group of gay friends living in San Francisco.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ef089948190902ec22f4d7bc932 completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6797954c8190ac05ee3db634efa7 completed May 9, 2026, 4:57 p.m.
NEDg Description generation batch_69ff68481ff881909c23ae20bd3a9ff8 completed May 9, 2026, 5 p.m.
NED2 Entity disambiguation (via description) batch_69ff6911a76c819088c8a86d2106b6c6 completed May 9, 2026, 5:04 p.m.
Created at: April 10, 2026, 4:15 a.m.