Triple
T1789481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commodore Amiga 2000 |
E39461
|
entity |
| Predicate | regionVariants |
P11942
|
FINISHED |
| Object | NTSC 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: NTSC model | Statement: [Commodore Amiga 2000, regionVariants, NTSC model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionVariants Context triple: [Commodore Amiga 2000, regionVariants, NTSC model]
-
A.
regionalVariantOf
chosen
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
-
B.
regionSpecialization
Indicates that a region is designated or recognized as being particularly focused on, adapted to, or specialized in a specific function, activity, or domain.
-
C.
regionException
Indicates an exception or exclusion to a rule, condition, or classification that applies specifically to a certain region or set of regions.
-
D.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
E.
regionName
Indicates the name assigned to a specific geographic or administrative region.
- 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_69a88631854081909723959921e45c2b |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab75457e54819096b8c6ae8c65550c |
completed | March 7, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69aa61d165688190924962a98e07ff69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:32 p.m.