Triple

T7304722
Position Surface form Disambiguated ID Type / Status
Subject SSSE3 E167944 entity
Predicate compatibleWith P203 FINISHED
Object SSE3 E164899 NE 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: SSE3 | Statement: [SSSE3, compatibleWith, SSE3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SSE3
Context triple: [SSSE3, compatibleWith, SSE3]
  • A. SSE3 chosen
    SSE3 (Streaming SIMD Extensions 3) is an Intel CPU instruction set extension that adds additional SIMD operations to improve performance in multimedia, gaming, and scientific applications.
  • B. SSSE3
    SSSE3 (Supplemental Streaming SIMD Extensions 3) is an Intel SIMD instruction set extension that enhances performance for multimedia, signal processing, and other parallelizable workloads.
  • C. SSE2
    SSE2 is an x86 processor instruction set extension introduced by Intel that adds advanced SIMD (Single Instruction, Multiple Data) capabilities for faster floating-point and integer computations.
  • D. SSE4.2
    SSE4.2 is an Intel x86 instruction set extension that adds advanced string, text-processing, and CRC instructions to improve performance in multimedia, gaming, and data-processing applications.
  • E. SSE4.1
    SSE4.1 is an Intel SIMD instruction set extension that adds advanced vector, integer, and floating-point operations to improve performance in multimedia, graphics, and data-processing applications.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c6888c820881909fc68f689fe1c251 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6ebd61c0c8190abb1368c9dfb1550 completed March 27, 2026, 8:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69c827651b7c81908f5dca5903183b7b completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 3:01 p.m.