Triple

T4276009
Position Surface form Disambiguated ID Type / Status
Subject ESP32 microcontrollers E97048 entity
Predicate hasVariant P455 FINISHED
Object ESP32 E97048 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: ESP32 | Statement: [ESP32 microcontrollers, hasVariant, ESP32]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ESP32
Context triple: [ESP32 microcontrollers, hasVariant, ESP32]
  • A. ESP32 microcontrollers chosen
    ESP32 microcontrollers are low-cost, low-power Wi-Fi and Bluetooth-enabled system-on-chips from Espressif, widely used for IoT, embedded, and hobbyist electronics projects.
  • B. CircuitPython
    CircuitPython is an open-source, beginner-friendly variant of Python designed by Adafruit for programming microcontrollers and embedded hardware.
  • C. ETH Board
    The ETH Board is the strategic leadership and supervisory body overseeing Switzerland’s federal institutes of technology, including ETH Zurich and EPFL.
  • D. Calliope mini
    Calliope mini is a small educational microcontroller board designed to teach children and beginners programming and electronics through interactive projects.
  • E. MicroPython
    MicroPython is a lean and efficient reimplementation of the Python 3 language designed to run on microcontrollers and other resource-constrained embedded systems.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3501d677481909e7416a1d2b0008c completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b3b52c8190ae7c05448faf5558 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:07 p.m.