Triple
T7935750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monochrome Display Adapter |
E184284
|
entity |
| Predicate | characterMatrix |
P64709
|
FINISHED |
| Object | 8×14 dot matrix 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: 8×14 dot matrix characters | Statement: [Monochrome Display Adapter, characterMatrix, 8×14 dot matrix characters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterMatrix Context triple: [Monochrome Display Adapter, characterMatrix, 8×14 dot matrix characters]
-
A.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
B.
character3
Indicates a tertiary or additional character role associated with an entity, typically the third distinct character linked within a given context or work.
-
C.
textCharacter
Indicates that one entity is a character (such as a letter, digit, or symbol) within a piece of text associated with another entity.
-
D.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
-
E.
characterCoverage
chosen
Indicates that one entity provides or includes sufficient representation or support for the characters (e.g., glyphs, symbols, or scripts) required or used by 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3aec394081909a9569c02ac372af |
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.