Triple

T11979881
Position Surface form Disambiguated ID Type / Status
Subject TelevisaUnivision E285129 entity
Predicate owns P347 FINISHED
Object ViX
ViX is a Spanish-language streaming service offering a wide range of movies, series, sports, and original content primarily for Hispanic audiences.
 E958068 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: ViX | Statement: [TelevisaUnivision, owns, ViX]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ViX
Context triple: [TelevisaUnivision, owns, ViX]
  • A. VIKI
    VIKI is the central artificial intelligence system and primary antagonist in the science fiction film "I, Robot," overseeing and controlling robots under a rigid interpretation of the Three Laws of Robotics.
  • B. Viks
    Viks is a shortened nickname commonly used to refer to the Vikings sports teams.
  • C. VIJO
    VIJO is the ICAO airport code assigned to Jodhpur Airport in Rajasthan, India.
  • D. VIR
    VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
  • E. VIKA
    VIKA is the ICAO airport code assigned to Kanpur Airport in Uttar Pradesh, India.
  • 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: ViX
Triple: [TelevisaUnivision, owns, ViX]
Generated description
ViX is a Spanish-language streaming service offering a wide range of movies, series, sports, and original content primarily for Hispanic audiences.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ViX
Target entity description: ViX is a Spanish-language streaming service offering a wide range of movies, series, sports, and original content primarily for Hispanic audiences.
  • A. VIKI
    VIKI is the central artificial intelligence system and primary antagonist in the science fiction film "I, Robot," overseeing and controlling robots under a rigid interpretation of the Three Laws of Robotics.
  • B. Viks
    Viks is a shortened nickname commonly used to refer to the Vikings sports teams.
  • C. VIJO
    VIJO is the ICAO airport code assigned to Jodhpur Airport in Rajasthan, India.
  • D. VIR
    VIR is the ICAO airline designator used to identify Virgin Atlantic in international aviation operations.
  • E. VIKA
    VIKA is the ICAO airport code assigned to Kanpur Airport in Uttar Pradesh, India.
  • 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_69d6ab2eaeb881909f7914758f859413 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90393cfb08190b5b45d3e5e32fad3 completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f47209bd088190bf4c7687c0a5eed6 completed May 1, 2026, 9:27 a.m.
NEDg Description generation batch_69f47b7ac4048190ae09f18f1a90338f completed May 1, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69f47db91f38819092b7b5c5e2bb489b completed May 1, 2026, 10:17 a.m.
Created at: April 8, 2026, 9:46 p.m.