Triple
T1635697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MDA |
E35355
|
entity |
| Predicate | characterCellResolution |
P30785
|
FINISHED |
| Object | 9×14 pixels |
—
|
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: 9×14 pixels | Statement: [MDA, characterCellResolution, 9×14 pixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterCellResolution Context triple: [MDA, characterCellResolution, 9×14 pixels]
-
A.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
B.
resolutionClass
Indicates the category or type of resolution applied to address or conclude a particular issue, conflict, or process.
-
C.
cellType
Indicates the classification relationship that specifies what type of cell an entity is or is associated with.
-
D.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
E.
zoningCharacter
Indicates how the regulatory or functional nature of a geographic area is defined or classified in terms of land-use zoning.
- 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_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. |
| PDg | Predicate description generation | batch_69a9607716b4819092187f8c08daaf31 |
completed | March 5, 2026, 10:52 a.m. |
Created at: March 4, 2026, 7:28 p.m.