Triple
T1635747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CGA |
E35356
|
entity |
| Predicate | textModeResolution |
P5732
|
FINISHED |
| Object | 40×25 characters |
—
|
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: 40×25 characters | Statement: [CGA, textModeResolution, 40×25 characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textModeResolution Context triple: [CGA, textModeResolution, 40×25 characters]
-
A.
textMode
Indicates that something operates, is displayed, or is processed in a mode where information is handled primarily as text rather than as graphics or other media.
-
B.
displayResolution
chosen
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
C.
textType
Indicates the classification of a text according to its type, format, or genre.
-
D.
texture
Indicates the surface quality or feel of an entity as perceived by touch or appearance, such as being smooth, rough, soft, or coarse.
-
E.
displayType
Indicates the manner or format in which something is presented, shown, or rendered.
- 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_69a886036bc081909ff5de16dbe5e8ea |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a96083e7308190abbf025fe8e43abb |
completed | March 5, 2026, 10:52 a.m. |
| PD | Predicate disambiguation | batch_69a907cac610819083cafd4396b6d66c |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:28 p.m.