Triple

T8289180
Position Surface form Disambiguated ID Type / Status
Subject Virtual Network Computing E193851 entity
Predicate compression P27672 FINISHED
Object supports various encoding schemes for screen data LITERAL FINISHED

How this triple was built (2 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: supports various encoding schemes for screen data | Statement: [Virtual Network Computing, compression, supports various encoding schemes for screen data]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: compression
Context triple: [Virtual Network Computing, compression, supports various encoding schemes for screen data]
  • A. compressionType chosen
    Indicates the method or format used to compress data or content in the relationship.
  • B. compressionRatio
    Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
  • C. compressionDomain
    Indicates a relationship where one entity serves as the domain or context within which another entity’s compression or compression-related process is defined or applied.
  • D. compressionScope
    Indicates the extent or range within which compression is applied to data or content.
  • E. compressionAxis
    Indicates the primary direction along which a force or process compresses an object or material.
  • F. None of above.

Provenance (3 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_69cb7c98e15c8190ac2a0b2a5ff834c9 completed March 31, 2026, 7:49 a.m.
PD Predicate disambiguation batch_69cb70b5b5348190b296e0ecec95de60 completed March 31, 2026, 6:59 a.m.
Created at: March 30, 2026, 5:52 p.m.