Triple
T1936432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liquid Retina XDR |
E41452
|
entity |
| Predicate | distinguishingFactor |
P14118
|
FINISHED |
| Object | mini-LED backlight with many dimming zones |
—
|
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: mini-LED backlight with many dimming zones | Statement: [Liquid Retina XDR, distinguishingFactor, mini-LED backlight with many dimming zones]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinguishingFactor Context triple: [Liquid Retina XDR, distinguishingFactor, mini-LED backlight with many dimming zones]
-
A.
distinction
Indicates that one entity is recognized, treated, or classified as different or separate from another.
-
B.
isDistinguishedBy
chosen
Indicates that one entity is characterized or set apart from others by a particular feature, quality, or attribute.
-
C.
uniformDistinction
Indicates that a clear and consistent difference is maintained between two or more entities within a given context.
-
D.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
E.
differentiatedFrom
Indicates that one entity is distinguished or set apart from another by identifying differences between them.
- 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_69a88649b24c819080047f26b6db2ded |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2c5f6e481909b2d95861e2098f9 |
completed | March 7, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69abaff07cf88190b4883c5f17f90abd |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.