Triple
T8552424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SNK hardware |
E202473
|
entity |
| Predicate | companySpecialization |
P63924
|
FINISHED |
| Object | arcade system boards |
—
|
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: arcade system boards | Statement: [SNK hardware, companySpecialization, arcade system boards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: companySpecialization Context triple: [SNK hardware, companySpecialization, arcade system boards]
-
A.
associatedCompanySpecialization
chosen
Indicates that a company is linked to a particular area of specialization or expertise.
-
B.
marketSpecialization
Indicates a relationship where an entity focuses its activities, products, or services on serving a specific segment or niche of a broader market.
-
C.
positionSpecialization
Indicates that one position is a more specialized or focused variant of another, broader position.
-
D.
underlyingCompanyBusinessFocus
Indicates the primary industry, sector, or type of business activity that the underlying company is focused on.
-
E.
specializationRegion
Indicates that something is specialized, adapted, or specifically applicable to a particular geographic or spatial 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_69ca832610e08190b3b6c6cd2c250255 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe8882704819094b688d46169433a |
completed | March 31, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69cbd113e05c81908f4f3fc1b5925164 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:19 p.m.