Triple

T30026569
Position Surface form Disambiguated ID Type / Status
Subject GeForce 8 Series E762895 entity
Predicate graphicsCoreCodename P140224 FINISHED
Object G80 (high-end)
G80 (high-end) is NVIDIA’s flagship GPU core used in the top-tier GeForce 8 Series graphics cards, known for introducing a unified shader architecture and significantly advancing gaming and graphics performance.
 E1897506 NE FINISHED

How this triple was built (3 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: G80 (high-end) | Statement: [GeForce 8 Series, graphicsCoreCodename, G80 (high-end)]
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: G80 (high-end)
Triple: [GeForce 8 Series, graphicsCoreCodename, G80 (high-end)]
Generated description
G80 (high-end) is NVIDIA’s flagship GPU core used in the top-tier GeForce 8 Series graphics cards, known for introducing a unified shader architecture and significantly advancing gaming and graphics performance.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: graphicsCoreCodename
Context triple: [GeForce 8 Series, graphicsCoreCodename, G80 (high-end)]
  • A. relatedCodename
    Indicates that one entity has an associated or connected codename that is contextually related to it.
  • B. hardwareCodename chosen
    Indicates that one entity is the internal or code name assigned to a particular hardware product or component.
  • C. microarchitectureCodename
    Indicates the codename assigned to a specific microarchitecture design used in a hardware component or processor.
  • D. predecessorCoreCodename
    Indicates that one core codename directly precedes another in a sequence or lineage of codenames.
  • E. servesCodename
    Indicates that one entity provides or uses another entity under a specific codename or alias.
  • F. None of above.

Provenance (6 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_69f2246ee6e48190b69e837b913b398a completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f679ac62ac8190b1ab93bf5803e0a9 completed May 2, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a273231a4d48190ada158d1f54bbaf1 completed June 8, 2026, 9:20 p.m.
NEDg Description generation batch_6a27369f226081909c756c1db665159a completed June 8, 2026, 9:39 p.m.
NED2 Entity disambiguation (via description) batch_6a2736f83b08819084c8fadd1fe1b6f2 completed June 8, 2026, 9:41 p.m.
PD Predicate disambiguation batch_69f66ec9919881908a187bfc7c4df192 completed May 2, 2026, 9:38 p.m.
Created at: April 29, 2026, 6:48 p.m.