Triple

T8860002
Position Surface form Disambiguated ID Type / Status
Subject Sega 32X E210861 entity
Predicate videoOutput P31524 FINISHED
Object RGB
RGB is a color model and video signal standard that represents images using separate red, green, and blue channels, commonly used for high-quality analog and digital display output.
 E24283 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: RGB | Statement: [Sega 32X, videoOutput, RGB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RGB
Context triple: [Sega 32X, videoOutput, RGB]
  • A. BGR
    BGR is the three-letter ISO 3166-1 alpha-3 country code assigned to Bulgaria.
  • B. BGR
    BGR is the three-letter IATA airport code for Bangor International Airport in Bangor, Maine, United States.
  • C. sRGB
    sRGB is a standard RGB color space widely used for digital images, displays, and the web to ensure consistent color reproduction across devices.
  • D. RWB
    RWB is the commonly used abbreviation for the Royal Winnipeg Ballet, one of Canada’s oldest and most renowned ballet companies.
  • E. HSB
    HSB is the National Rail station code for Helsby railway station in Cheshire, England.
  • 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: RGB
Triple: [Sega 32X, videoOutput, RGB]
Generated description
RGB is a color model and video signal standard that represents images using separate red, green, and blue channels, commonly used for high-quality analog and digital display output.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: RGB
Target entity description: RGB is a color model and video signal standard that represents images using separate red, green, and blue channels, commonly used for high-quality analog and digital display output.
  • A. BGR
    BGR is the three-letter ISO 3166-1 alpha-3 country code assigned to Bulgaria.
  • B. BGR
    BGR is the three-letter IATA airport code for Bangor International Airport in Bangor, Maine, United States.
  • C. sRGB chosen
    sRGB is a standard RGB color space widely used for digital images, displays, and the web to ensure consistent color reproduction across devices.
  • D. RWB
    RWB is the commonly used abbreviation for the Royal Winnipeg Ballet, one of Canada’s oldest and most renowned ballet companies.
  • E. HSB
    HSB is the National Rail station code for Helsby railway station in Cheshire, England.
  • F. None of above.

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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60e712d08190bfb1c4ba3acaea90 completed April 1, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0b94f5481909902b5fa405a502f completed April 3, 2026, 11:12 a.m.
NEDg Description generation batch_69cfa1714b4081909035c9b15c82c1be completed April 3, 2026, 11:16 a.m.
NED2 Entity disambiguation (via description) batch_69cfa24be80481909e2b575f99cd1dc4 completed April 3, 2026, 11:19 a.m.
Created at: March 30, 2026, 6:50 p.m.