Triple

T8269999
Position Surface form Disambiguated ID Type / Status
Subject Bell Media E193402 entity
Predicate owns P347 FINISHED
Object Noovo
Noovo is a Canadian French-language television network offering a mix of entertainment, reality shows, and local programming.
 E722788 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: Noovo | Statement: [Bell Media, owns, Noovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Noovo
Context triple: [Bell Media, owns, Noovo]
  • A. NOVN
    NOVN is the stock ticker symbol for Novartis, a major Swiss multinational pharmaceutical company known for developing and manufacturing innovative medicines.
  • B. Nouvel
    Nouvel is a French surname most prominently associated with Jean Nouvel, the renowned contemporary architect known for his innovative and experimental building designs worldwide.
  • C. Novaggio
    Novaggio is a small municipality in the canton of Ticino in southern Switzerland, known for its scenic hillside setting above Lake Lugano.
  • D. Neox
    Neox is a Spanish television channel owned by Atresmedia that primarily targets young audiences with a mix of series, films, and entertainment programs.
  • E. Nutun
    Nutun was a prominent Indian film actress celebrated for her nuanced performances and strong female roles in classic Hindi cinema.
  • 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: Noovo
Triple: [Bell Media, owns, Noovo]
Generated description
Noovo is a Canadian French-language television network offering a mix of entertainment, reality shows, and local programming.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Noovo
Target entity description: Noovo is a Canadian French-language television network offering a mix of entertainment, reality shows, and local programming.
  • A. NOVN
    NOVN is the stock ticker symbol for Novartis, a major Swiss multinational pharmaceutical company known for developing and manufacturing innovative medicines.
  • B. Nouvel
    Nouvel is a French surname most prominently associated with Jean Nouvel, the renowned contemporary architect known for his innovative and experimental building designs worldwide.
  • C. Novaggio
    Novaggio is a small municipality in the canton of Ticino in southern Switzerland, known for its scenic hillside setting above Lake Lugano.
  • D. Neox
    Neox is a Spanish television channel owned by Atresmedia that primarily targets young audiences with a mix of series, films, and entertainment programs.
  • E. Nutun
    Nutun was a prominent Indian film actress celebrated for her nuanced performances and strong female roles in classic Hindi cinema.
  • 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.