Triple

T22062858
Position Surface form Disambiguated ID Type / Status
Subject BSF E545194 entity
Predicate supportsFramework P9089 FINISHED
Object Generic Bootstrapping Architecture NE NERFINISHED

How this triple was built (3 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: Generic Bootstrapping Architecture | Statement: [BSF, supportsFramework, Generic Bootstrapping Architecture]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Generic Bootstrapping Architecture
Context triple: [BSF, supportsFramework, Generic Bootstrapping Architecture]
  • A. Omni-Path Architecture
    Omni-Path Architecture is a high-performance computing interconnect technology developed by Intel to provide low-latency, high-bandwidth communication in large-scale supercomputing and data center environments.
  • B. Reformer architecture
    The Reformer architecture is a neural network model that improves Transformer efficiency by using locality-sensitive hashing attention and reversible layers to greatly reduce memory and computational costs.
  • C. Alpha architecture
    Alpha architecture is a 64-bit RISC microprocessor architecture known for its high performance and use in workstations and servers in the 1990s and early 2000s.
  • D. Computation Independent Model
    A Computation Independent Model is a high-level representation of a system that focuses on its environment and requirements without detailing computational or implementation aspects.
  • E. The Architecture Machine
    The Architecture Machine is a seminal book by Nicholas Negroponte that explores the concept of interactive, computer-based design systems and their implications for architecture and human–machine collaboration.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Generic Bootstrapping Architecture
Target entity description: Generic Bootstrapping Architecture is a flexible, reusable software framework designed to initialize and configure applications or systems in a standardized, extensible way.
  • A. Omni-Path Architecture
    Omni-Path Architecture is a high-performance computing interconnect technology developed by Intel to provide low-latency, high-bandwidth communication in large-scale supercomputing and data center environments.
  • B. Reformer architecture
    The Reformer architecture is a neural network model that improves Transformer efficiency by using locality-sensitive hashing attention and reversible layers to greatly reduce memory and computational costs.
  • C. Alpha architecture
    Alpha architecture is a 64-bit RISC microprocessor architecture known for its high performance and use in workstations and servers in the 1990s and early 2000s.
  • D. Computation Independent Model
    A Computation Independent Model is a high-level representation of a system that focuses on its environment and requirements without detailing computational or implementation aspects.
  • E. The Architecture Machine
    The Architecture Machine is a seminal book by Nicholas Negroponte that explores the concept of interactive, computer-based design systems and their implications for architecture and human–machine collaboration.
  • F. None of above. chosen

Provenance (2 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_69e11e3377c48190890c17407b9527d6 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f1285e8c688190b701e417893cc148 completed April 28, 2026, 9:36 p.m.
Created at: April 16, 2026, 8:27 p.m.