Triple
T7935937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM Color/Graphics Monitor Adapter |
E184288
|
entity |
| Predicate | textCharacterCellSize |
P30785
|
FINISHED |
| Object | 8×8 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: 8×8 pixels | Statement: [IBM Color/Graphics Monitor Adapter, textCharacterCellSize, 8×8 pixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textCharacterCellSize Context triple: [IBM Color/Graphics Monitor Adapter, textCharacterCellSize, 8×8 pixels]
-
A.
characterCellResolution
chosen
Indicates a relationship where the visual or logical representation of characters is determined or adjusted at the level of individual cells (e.g., grid units or display slots).
-
B.
textCharacter
Indicates that one entity is a character (such as a letter, digit, or symbol) within a piece of text associated with another entity.
-
C.
characterSetSize
Indicates the total number of distinct characters contained in or allowed by a given character set.
-
D.
cellSize
Indicates the physical dimensions or volume of a cell in a biological or computational context.
-
E.
graphicCharactersCount
Indicates the number of printable (non-control) characters present in a given text or string.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aede3cc81908b0d3b54e68997b9 |
completed | March 31, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:08 p.m.