Triple

T8289428
Position Surface form Disambiguated ID Type / Status
Subject HLSL E193856 entity
Predicate relatedTo P37 FINISHED
Object Cg
Cg is a high-level shading language developed by NVIDIA for programming graphics processing units, similar in design and purpose to HLSL.
 E724346 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: Cg | Statement: [HLSL, relatedTo, Cg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Cg
Context triple: [HLSL, relatedTo, Cg]
  • A. CGR
    CGR is the IATA airport code for Campo Grande International Airport in Campo Grande, Brazil.
  • B. GLC
    The GLC is a compact luxury crossover SUV produced by Mercedes-Benz, positioned as one of the brand’s core premium utility vehicles.
  • C. GLC
    GLC is a prominent and historic law college in Mumbai, India, officially known as Government Law College.
  • D. GLC
    GLC is a Chicago-based rapper and longtime Kanye West collaborator known for his appearances on early Kanye albums and his affiliation with the G.O.O.D. Music collective.
  • E. GLC
    GLC is the National Rail station code for Glasgow Central, a major railway terminus in Glasgow, Scotland.
  • 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: Cg
Triple: [HLSL, relatedTo, Cg]
Generated description
Cg is a high-level shading language developed by NVIDIA for programming graphics processing units, similar in design and purpose to HLSL.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Cg
Target entity description: Cg is a high-level shading language developed by NVIDIA for programming graphics processing units, similar in design and purpose to HLSL.
  • A. CGR
    CGR is the IATA airport code for Campo Grande International Airport in Campo Grande, Brazil.
  • B. GLC
    The GLC is a compact luxury crossover SUV produced by Mercedes-Benz, positioned as one of the brand’s core premium utility vehicles.
  • C. GLC
    GLC is a prominent and historic law college in Mumbai, India, officially known as Government Law College.
  • D. GLC
    GLC is a Chicago-based rapper and longtime Kanye West collaborator known for his appearances on early Kanye albums and his affiliation with the G.O.O.D. Music collective.
  • E. GLC
    GLC is the National Rail station code for Glasgow Central, a major railway terminus in Glasgow, Scotland.
  • 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_69ca82e32db481908b72f3804fa71152 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7c99fdd48190a3f304237be609a0 completed March 31, 2026, 7:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd68898610819091a76f89cd2a6aa2 completed April 1, 2026, 6:48 p.m.
NEDg Description generation batch_69cd6d567c3c81908a7ec5bc13be529d completed April 1, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_69cd7e2bdae08190adc51e904e85695e completed April 1, 2026, 8:21 p.m.
Created at: March 30, 2026, 5:52 p.m.