Triple
T33051974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LCD |
E845749
|
entity |
| Predicate | energyConsumptionComparedToCRT |
P125223
|
FINISHED |
| Object | lower |
—
|
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 | Statement: [LCD, energyConsumptionComparedToCRT, lower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyConsumptionComparedToCRT Context triple: [LCD, energyConsumptionComparedToCRT, lower]
-
A.
advantageOverCRT
chosen
Indicates that one entity possesses a benefit, superiority, or favorable quality when compared to CRT.
-
B.
hasBetterColorReproductionThan
Indicates that one entity produces more accurate or higher-quality color representation than another entity.
-
C.
typicalEfficiencyComparedToPredecessor
Indicates how the usual or average efficiency of something compares to that of its predecessor.
-
D.
operatingSpeedComparedToContemporaries
Indicates how an entity’s operating speed compares relative to other similar entities from the same time period.
-
E.
powerConsumptionWatts
Indicates the amount of electrical power an entity uses, measured in watts, during its operation.
- F. None of above.
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_69f3495242e48190996a2cb2beab5455 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:24 a.m.