Triple
T16852869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LCD TV |
E409716
|
entity |
| Predicate | advantageOverPlasma |
P125222
|
FINISHED |
| Object | lower power consumption |
—
|
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 power consumption | Statement: [LCD TV, advantageOverPlasma, lower power consumption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advantageOverPlasma Context triple: [LCD TV, advantageOverPlasma, lower power consumption]
-
A.
advantageOverEcho
Indicates that one entity possesses an advantage or superiority over another entity referred to as Echo.
-
B.
isStrongerProtectionThan
Indicates that one form of protection provides a higher level of security, defense, or safeguarding compared to another.
-
C.
isStrongerThan
Indicates that one entity possesses greater physical power, force, or effectiveness than another entity.
-
D.
powerplantAdvantage
Indicates that one power plant has an advantage or beneficial characteristic over another in a given context.
-
E.
hasGreaterNoiseReductionThan
Indicates that one entity provides a higher level of noise reduction compared to 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37abadc81909d02d329403497d6 |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e355722040819098830dabf207ecd6 |
completed | April 18, 2026, 9:57 a.m. |
Created at: April 10, 2026, 5:24 a.m.