Triple

T8270001
Position Surface form Disambiguated ID Type / Status
Subject Bell Media E193402 entity
Predicate owns P347 FINISHED
Object Much
Much is a Canadian specialty television channel best known for its music-related programming and pop culture content, formerly branded as MuchMusic.
 E722789 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: Much | Statement: [Bell Media, owns, Much]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Much
Context triple: [Bell Media, owns, Much]
  • A. Most
    Most is an industrial city in the Ústí nad Labem Region of the Czech Republic, historically known for coal mining and extensive postwar urban redevelopment.
  • B. Major
    Major is a common English surname notably borne by former UK Prime Minister John Major and his wife, charity campaigner Norma Major.
  • C. Major
    Major is a mid-level commissioned officer rank in the Portuguese Air Force, typically positioned above captain and below lieutenant colonel.
  • D. Massive
    Massive is an alias used by the pioneering British trip hop group Massive Attack, known for their atmospheric, genre-blending sound.
  • E. MOST
    MOST is a science and technology museum in Syracuse, New York, featuring interactive exhibits and educational programs focused on STEM learning.
  • 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: Much
Triple: [Bell Media, owns, Much]
Generated description
Much is a Canadian specialty television channel best known for its music-related programming and pop culture content, formerly branded as MuchMusic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Much
Target entity description: Much is a Canadian specialty television channel best known for its music-related programming and pop culture content, formerly branded as MuchMusic.
  • A. Most
    Most is an industrial city in the Ústí nad Labem Region of the Czech Republic, historically known for coal mining and extensive postwar urban redevelopment.
  • B. Major
    Major is a common English surname notably borne by former UK Prime Minister John Major and his wife, charity campaigner Norma Major.
  • C. Major
    Major is a mid-level commissioned officer rank in the Portuguese Air Force, typically positioned above captain and below lieutenant colonel.
  • D. Massive
    Massive is an alias used by the pioneering British trip hop group Massive Attack, known for their atmospheric, genre-blending sound.
  • E. MOST
    MOST is a science and technology museum in Syracuse, New York, featuring interactive exhibits and educational programs focused on STEM learning.
  • 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_69ca82e14ae481908ffdb822cd2192bc completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb795243fc8190a66afef7476e1147 completed March 31, 2026, 7:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd683d04e081908b0ce81e866f0311 completed April 1, 2026, 6:47 p.m.
NEDg Description generation batch_69cd6c21172481908dc04b85ee4370a8 completed April 1, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_69cd7df568788190a5a219baa65a6a19 completed April 1, 2026, 8:20 p.m.
Created at: March 30, 2026, 5:50 p.m.