Triple

T8865285
Position Surface form Disambiguated ID Type / Status
Subject The Black Keys E211002 entity
Predicate notableSong P4 FINISHED
Object Lo/Hi
"Lo/Hi" is a bluesy rock song by American rock duo The Black Keys, known for its gritty guitar riffs and soulful, gospel-tinged backing vocals.
 E762393 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: Lo/Hi | Statement: [The Black Keys, notableSong, Lo/Hi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lo/Hi
Context triple: [The Black Keys, notableSong, Lo/Hi]
  • A. How Low
    "How Low" is a popular hip-hop single by American rapper Ludacris, known for its catchy hook and heavy club-oriented production.
  • B. High and Low
    High and Low is a 1963 Japanese crime thriller film by Akira Kurosawa that explores class disparity and moral conflict through a tense kidnapping drama.
  • C. LO
    LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
  • D. LO
    LO is the vehicle registration code used on license plates for vehicles registered in the Province of Lodi in Italy.
  • E. LO
    LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
  • 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: Lo/Hi
Triple: [The Black Keys, notableSong, Lo/Hi]
Generated description
"Lo/Hi" is a bluesy rock song by American rock duo The Black Keys, known for its gritty guitar riffs and soulful, gospel-tinged backing vocals.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lo/Hi
Target entity description: "Lo/Hi" is a bluesy rock song by American rock duo The Black Keys, known for its gritty guitar riffs and soulful, gospel-tinged backing vocals.
  • A. How Low
    "How Low" is a popular hip-hop single by American rapper Ludacris, known for its catchy hook and heavy club-oriented production.
  • B. High and Low
    High and Low is a 1963 Japanese crime thriller film by Akira Kurosawa that explores class disparity and moral conflict through a tense kidnapping drama.
  • C. LO
    LO was the New York Stock Exchange ticker symbol for Lorillard Tobacco Company, a major American tobacco manufacturer best known for brands like Newport.
  • D. LO
    LO is the vehicle registration code used on license plates for vehicles registered in the Province of Lodi in Italy.
  • E. LO
    LO is Norway’s largest and most influential trade union confederation, representing a broad spectrum of workers across multiple sectors.
  • 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_69ca838d3c7c8190a849566d5afd2b11 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610569d08190b108107dfe397f18 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0d311148190823cc047e2908bc0 completed April 3, 2026, 11:13 a.m.
NEDg Description generation batch_69cfa1714b4081909035c9b15c82c1be completed April 3, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69cfa24efdc081908ef615305deb5b15 completed April 3, 2026, 11:19 a.m.
Created at: March 30, 2026, 6:51 p.m.