Triple
T16852871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LCD TV |
E409716
|
entity |
| Predicate | advantageOverCRT |
P125223
|
FINISHED |
| Object | thinner design |
—
|
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: thinner design | Statement: [LCD TV, advantageOverCRT, thinner design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: advantageOverCRT Context triple: [LCD TV, advantageOverCRT, thinner design]
-
A.
hasBetterColorReproductionThan
Indicates that one entity produces more accurate or higher-quality color representation than another entity.
-
B.
contrastCapability
Indicates a relationship where one entity’s capabilities are compared or set in opposition to another’s, highlighting differences in what they can do or achieve.
-
C.
supportsDisplayTechnology
Indicates that one entity is compatible with, or capable of operating using, a specified display technology.
-
D.
visualTechnology
Indicates a relationship where one entity is a technology used to capture, process, display, or otherwise handle visual information for another entity or context.
-
E.
advantageOverHDD
Indicates that one entity possesses a benefit, superiority, or improvement when compared to a hard disk drive (HDD).
- 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.