Triple
T14443357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LG smart TVs |
E358140
|
entity |
| Predicate | hasScreenSizeRange |
P12465
|
FINISHED |
| Object | small to large screen sizes |
—
|
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: small to large screen sizes | Statement: [LG smart TVs, hasScreenSizeRange, small to large screen sizes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScreenSizeRange Context triple: [LG smart TVs, hasScreenSizeRange, small to large screen sizes]
-
A.
hasBottomScreenSize
Indicates that an entity has a bottom screen whose size (e.g., dimensions or diagonal measurement) is specified by the related value or object.
-
B.
hasTopScreenSize
Indicates that an entity (typically a device) possesses a top screen with a specified size or dimension.
-
C.
hasScreenType
Indicates the specific kind or category of screen associated with or used by an entity.
-
D.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
-
E.
includesSizeRange
chosen
Indicates that one entity specifies or covers a particular range of sizes associated with another entity.
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de915d28ec81909e72124e9dd67bfb |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.