Triple
T8521089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas Instruments SN76489 |
E201693
|
entity |
| Predicate | noiseSource |
P83120
|
FINISHED |
| Object | linear feedback shift register (LFSR) |
—
|
LITERAL 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: linear feedback shift register (LFSR) | Statement: [Texas Instruments SN76489, noiseSource, linear feedback shift register (LFSR)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseSource Context triple: [Texas Instruments SN76489, noiseSource, linear feedback shift register (LFSR)]
-
A.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
B.
noiseCompliance
Indicates that an entity adheres to specified rules or standards governing acceptable noise levels or sound emissions.
-
C.
noisePolicy
Indicates the rules or constraints governing acceptable noise levels or noise-related behavior in a given context.
-
D.
targetsNoiseType
Indicates that an entity is directed at, designed for, or specifically affects a particular type or category of noise.
-
E.
soundEngine
Indicates that one entity functions as or provides the sound engine (audio processing or synthesis system) used by another entity.
- F. None of above. chosen
Provenance (4 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62a490481908ee0ad4ba9a94682 |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30d453481908f897ed2b06e7534 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:16 p.m.