Triple

T14819649
Position Surface form Disambiguated ID Type / Status
Subject UltraSPARC IV E348410 entity
Predicate ecosystem P964 FINISHED
Object SPARC platform E68040 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: SPARC platform | Statement: [UltraSPARC IV, ecosystem, SPARC platform]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SPARC platform
Context triple: [UltraSPARC IV, ecosystem, SPARC platform]
  • A. SPARC microprocessor architecture chosen
    The SPARC microprocessor architecture is a RISC-based instruction set architecture widely used in high-performance and enterprise servers, originally created to power scalable, multi-processor systems.
  • B. SPARC
    SPARC is a core project of the World Climate Research Programme that focuses on understanding the role of the stratosphere and upper troposphere in the Earth’s climate system.
  • C. SPARC V9
    SPARC V9 is a 64-bit RISC instruction set architecture developed by Sun Microsystems for high-performance, scalable SPARC processors.
  • D. SPARC64 VII
    SPARC64 VII is a 64-bit RISC microprocessor from Fujitsu’s SPARC family, designed for high-performance, enterprise-class UNIX servers.
  • E. SPARC64 X
    SPARC64 X is a 64-bit SPARC microprocessor developed by Fujitsu for high-performance enterprise and server computing workloads.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe4cf38819090f25ef045351d5d completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe64f8b4148190bc24f9a307178419 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:50 a.m.