Triple

T21001550
Position Surface form Disambiguated ID Type / Status
Subject Miami Sound Machine E517301 entity
Predicate notableWork P4 FINISHED
Object 1-2-3
1-2-3 is a mid-1980s pop song by Miami Sound Machine that blends Latin rhythms with dance-pop and helped cement the group’s mainstream success.
 E1462054 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: 1-2-3 | Statement: [Miami Sound Machine, notableWork, 1-2-3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: 1-2-3
Context triple: [Miami Sound Machine, notableWork, 1-2-3]
  • A. 1-2-3
    1-2-3 is a punk rock song by The Professionals, known for its driving energy and classic early-1980s UK punk sound.
  • B. One, Two, Three
    One, Two, Three is a 1961 fast-paced Cold War comedy film set in West Berlin, known for its rapid-fire dialogue and satirical take on East–West tensions.
  • C. Count to Three
    "Count to Three" is a song by the American rock band Emo, known for its emotionally charged lyrics and melodic instrumentation.
  • D. Three and One
    "Three and One" is a jazz composition by trumpeter and bandleader Thad Jones, recognized as one of his signature works in the modern big band repertoire.
  • E. Three Up, Two Down
    Three Up, Two Down is a British television sitcom best known for its comedic portrayal of two very different families forced to share a suburban house.
  • 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: 1-2-3
Triple: [Miami Sound Machine, notableWork, 1-2-3]
Generated description
1-2-3 is a mid-1980s pop song by Miami Sound Machine that blends Latin rhythms with dance-pop and helped cement the group’s mainstream success.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: 1-2-3
Target entity description: 1-2-3 is a mid-1980s pop song by Miami Sound Machine that blends Latin rhythms with dance-pop and helped cement the group’s mainstream success.
  • A. 1-2-3
    1-2-3 is a punk rock song by The Professionals, known for its driving energy and classic early-1980s UK punk sound.
  • B. One, Two, Three
    One, Two, Three is a 1961 fast-paced Cold War comedy film set in West Berlin, known for its rapid-fire dialogue and satirical take on East–West tensions.
  • C. Count to Three
    "Count to Three" is a song by the American rock band Emo, known for its emotionally charged lyrics and melodic instrumentation.
  • D. Three and One
    "Three and One" is a jazz composition by trumpeter and bandleader Thad Jones, recognized as one of his signature works in the modern big band repertoire.
  • E. Three Up, Two Down
    Three Up, Two Down is a British television sitcom best known for its comedic portrayal of two very different families forced to share a suburban house.
  • 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_69e0b5006e2881909fc2383f841740cc completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc25c1f8819086bdbfd89d390f5f completed April 21, 2026, 4:25 a.m.
NED1 Entity disambiguation (via context triple) batch_6a093b545f5081909152211b7e03bea1 completed May 17, 2026, 3:51 a.m.
NEDg Description generation batch_6a093e5b743881908dea54f627f2a220 completed May 17, 2026, 4:04 a.m.
NED2 Entity disambiguation (via description) batch_6a093ebe37cc8190961b02f8f12ce4b0 completed May 17, 2026, 4:06 a.m.
Created at: April 16, 2026, 1:52 p.m.