Triple

T7079162
Position Surface form Disambiguated ID Type / Status
Subject SSE3 E164899 entity
Predicate successor P78 FINISHED
Object SSSE3 E167944 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: SSSE3 | Statement: [SSE3, successor, SSSE3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SSSE3
Context triple: [SSE3, successor, SSSE3]
  • A. SSSE3 chosen
    SSSE3 (Supplemental Streaming SIMD Extensions 3) is an Intel SIMD instruction set extension that enhances performance for multimedia, signal processing, and other parallelizable workloads.
  • B. SSE3
    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.
  • 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. Intel SSE
    Intel SSE is a set of SIMD (Single Instruction, Multiple Data) instruction extensions for x86 processors designed to accelerate multimedia, gaming, and scientific applications through parallel data processing.
  • 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_69c6887cbc6c8190bdfac42d940f4d8a completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e4ef47d48190b31125d1b57f7bec completed March 27, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79c8f11a48190a2a1f6ad99dc04b9 completed March 28, 2026, 9:17 a.m.
Created at: March 27, 2026, 2:40 p.m.