Triple
T22505089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STSPIN |
E556367
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | STSPIN32G4 |
—
|
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: STSPIN32G4 | Statement: [STSPIN, hasMember, STSPIN32G4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: STSPIN32G4 Context triple: [STSPIN, hasMember, STSPIN32G4]
-
A.
STSPIN32F025x
STSPIN32F025x is a family of STMicroelectronics integrated motor driver and control ICs that combine an STM32 microcontroller core with power stage and analog peripherals for driving three-phase motors.
-
B.
STSPIN
chosen
STSPIN is a family of motor driver integrated circuits from STMicroelectronics designed for controlling stepper, DC, and brushless motors in various applications.
-
C.
G3-PLC
G3-PLC is an international power line communication standard designed for robust, long-range, low-data-rate networking over existing electrical power lines, widely used in smart grid and smart metering applications.
-
D.
LM32
LM32 is a 32-bit soft microprocessor core architecture developed by Lattice Semiconductor, commonly used in FPGA-based embedded systems.
-
E.
ESP32-S3
ESP32-S3 is a low-power, dual-core Wi-Fi and Bluetooth LE microcontroller from Espressif designed for AI acceleration and advanced IoT applications.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15d5bf0f0819093426d83ebd80ef0 |
completed | April 29, 2026, 1:22 a.m. |
Created at: April 16, 2026, 8:50 p.m.