Triple

T12280942
Position Surface form Disambiguated ID Type / Status
Subject compiler-rt E292713 entity
Predicate target P860 FINISHED
Object RISC-V E37329 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: RISC-V | Statement: [compiler-rt, target, RISC-V]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RISC-V
Context triple: [compiler-rt, target, RISC-V]
  • A. RISC-V chosen
    RISC-V is an open, extensible instruction set architecture (ISA) based on the reduced instruction set computing (RISC) principles, widely used for research, embedded systems, and increasingly general-purpose computing.
  • B. RISC-V International
    RISC-V International is the global nonprofit consortium that oversees the development, standardization, and promotion of the open RISC-V instruction set architecture.
  • C. SiFive
    SiFive is a semiconductor company known for designing customizable RISC‑V processor cores and platforms used in a wide range of computing applications.
  • D. Spike RISC-V ISA simulator
    Spike RISC-V ISA simulator is the official reference software simulator for the RISC-V instruction set architecture, used to validate and test RISC-V implementations.
  • E. RISC
    RISC is an Austrian research institute specializing in symbolic computation, computer algebra, and related areas of mathematics and computer science.
  • 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cf2b09c81908a11581d33f65be0 completed April 10, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62a97614c8190b67e07df3e424e32 completed May 2, 2026, 4:47 p.m.
Created at: April 8, 2026, 9:52 p.m.