Triple

T17674994
Position Surface form Disambiguated ID Type / Status
Subject Nerves E440622 entity
Predicate supportsHardware P5090 FINISHED
Object BeagleBone boards NE NERFINISHED

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: BeagleBone boards | Statement: [Nerves, supportsHardware, BeagleBone boards]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BeagleBone boards
Context triple: [Nerves, supportsHardware, BeagleBone boards]
  • A. BeagleBone Black chosen
    BeagleBone Black is a low-cost, community-supported single-board computer based on an ARM Cortex-A8 processor, commonly used for embedded systems, robotics, and hardware prototyping.
  • B. BeagleBoard
    BeagleBoard is a low-power, open-hardware single-board computer designed for embedded systems, prototyping, and educational use.
  • C. Pandaboard
    Pandaboard is a low-power, ARM-based single-board computer designed for development and experimentation with operating systems and embedded applications.
  • D. Curiosity development board
    The Curiosity development board is a low-cost, feature-rich prototyping platform from Microchip designed to simplify evaluation and development with PIC microcontrollers.
  • E. Raspberry Pi
    Raspberry Pi is a low-cost, credit card–sized single-board computer widely used for education, DIY electronics projects, and lightweight computing tasks.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46f6cca54819094ea0bed1517724e completed April 19, 2026, 6 a.m.
Created at: April 10, 2026, 10 a.m.