Triple
T29182409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hang-On |
E739778
|
entity |
| Predicate | arcadeCabinetType |
P21145
|
FINISHED |
| Object | sit-down cabinet |
—
|
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: sit-down cabinet | Statement: [Hang-On, arcadeCabinetType, sit-down cabinet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arcadeCabinetType Context triple: [Hang-On, arcadeCabinetType, sit-down cabinet]
-
A.
arcadeHardwareDeveloper
Indicates that an entity is responsible for designing or developing hardware used in arcade game systems.
-
B.
cabinetType
chosen
Indicates the specific kind or category of cabinet associated with an entity.
-
C.
hasArcades
Indicates that one entity features or contains arcaded structures (a series of arches or covered passageways) associated with another entity.
-
D.
notableArcadeGame
Indicates that the subject is an arcade game that is particularly famous, influential, or otherwise noteworthy.
-
E.
typeOfGamblingVenue
Indicates that one entity is a specific kind or category of gambling venue in relation to 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_69f07cb74c2c8190ad396487fcb4fde6 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f66384473c81909fb9ff9037f56b67 |
completed | May 2, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69f660f2e3708190ab658652bcfc04d0 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 11:58 a.m.