Triple
T8521088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas Instruments SN76489 |
E201693
|
entity |
| Predicate | volumeLevels |
P83119
|
FINISHED |
| Object | 16 discrete volume steps |
—
|
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: 16 discrete volume steps | Statement: [Texas Instruments SN76489, volumeLevels, 16 discrete volume steps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: volumeLevels Context triple: [Texas Instruments SN76489, volumeLevels, 16 discrete volume steps]
-
A.
volume
Indicates the amount of three-dimensional space an entity occupies or contains.
-
B.
hasSpeechLevels
Indicates that a language, dialect, or communicative system distinguishes different levels or styles of speech used according to social context, formality, or relative status between speakers.
-
C.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
D.
soundAmplification
Indicates that one entity increases the loudness or intensity of another entity’s sound.
-
E.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of 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.