Triple
T20165225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Family Computer |
E491809
|
entity |
| Predicate | regionExclusive |
P118359
|
FINISHED |
| Object | Japan-only base model |
—
|
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: Japan-only base model | Statement: [Family Computer, regionExclusive, Japan-only base model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionExclusive Context triple: [Family Computer, regionExclusive, Japan-only base model]
-
A.
regionExclusiveFeatures
chosen
Indicates that certain features, services, or options are available only within specific geographic regions and not accessible elsewhere.
-
B.
regionException
Indicates an exception or exclusion to a rule, condition, or classification that applies specifically to a certain region or set of regions.
-
C.
regionExposure
Indicates that an entity is subject to or affected by exposure within a specific geographic or spatial region.
-
D.
excludesRegion
Indicates that one entity explicitly omits, leaves out, or does not apply to a specified region or geographic area.
-
E.
regionOpposedExpansionIn
Indicates that a region actively resisted or opposed the expansion of another entity into its territory or sphere of influence.
- 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_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. |
Created at: April 11, 2026, 11:35 p.m.