Triple
T31498133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S-Cinetone |
E803603
|
entity |
| Predicate | disadvantageComparedToSLog3 |
P171706
|
FINISHED |
| Object | lower dynamic range |
—
|
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: lower dynamic range | Statement: [S-Cinetone, disadvantageComparedToSLog3, lower dynamic range]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disadvantageComparedToSLog3 Context triple: [S-Cinetone, disadvantageComparedToSLog3, lower dynamic range]
-
A.
disadvantageComparedToHDD
Indicates that one entity is less favorable or performs worse than a hard disk drive (HDD) in some specified aspect or context.
-
B.
disadvantageComparedToSATA
Indicates that something has a drawback, limitation, or weaker performance when compared to SATA.
-
C.
hasGreaterNoiseReductionThan
Indicates that one entity provides a higher level of noise reduction compared to another entity.
-
D.
isLessEfficientThan
Indicates that one entity performs a task or uses resources with lower efficiency compared to another entity.
-
E.
operatingSpeedComparedToContemporaries
Indicates how an entity’s operating speed compares relative to other similar entities from the same time period.
- 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_69f348cae52081909fa8e5f697523ae3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a1eac8688190afdf5732cedf086d |
completed | May 3, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69f69fe82e5c81909da9db0a2f3bba6d |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a0e920cc8190a943fdd0594906c5 |
completed | May 3, 2026, 1:12 a.m. |
Created at: April 30, 2026, 9:42 p.m.