Triple
T20165744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ricoh 2C02 PPU |
E491820
|
entity |
| Predicate | nameTableMirroring |
P138926
|
FINISHED |
| Object | controlled by cartridge wiring |
—
|
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: controlled by cartridge wiring | Statement: [Ricoh 2C02 PPU, nameTableMirroring, controlled by cartridge wiring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameTableMirroring Context triple: [Ricoh 2C02 PPU, nameTableMirroring, controlled by cartridge wiring]
-
A.
mirroredBy
Indicates that one entity serves as a reflective counterpart or reversed representation of another.
-
B.
mirroredAt
Indicates that one entity is a mirror image or reflection of another entity with respect to a specified axis, plane, or point.
-
C.
mirrorType
Indicates that one entity is a specific kind or category of mirror in relation to another entity.
-
D.
mirrorCount
Indicates the number of mirrors associated with or present in relation to a given entity or context.
-
E.
tableName
Indicates the name assigned to a database table that participates in the described relationship or operation.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e668442d2c81908bb1a0fac9895b5e |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56700b1a08190ace53cf95827d72d |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:35 p.m.