Triple
T8472990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sega Saturn |
E200320
|
entity |
| Predicate | arcadeBoardRelation |
P82814
|
FINISHED |
| Object | related to Sega Model 2 hardware |
—
|
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: related to Sega Model 2 hardware | Statement: [Sega Saturn, arcadeBoardRelation, related to Sega Model 2 hardware]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arcadeBoardRelation Context triple: [Sega Saturn, arcadeBoardRelation, related to Sega Model 2 hardware]
-
A.
hasArcades
Indicates that one entity features or contains arcaded structures (a series of arches or covered passageways) associated with another entity.
-
B.
numberOfAreaBoards
Indicates the total count of area boards associated with or defined for a given entity or context.
-
C.
associatedWithArena
Indicates a relationship in which an entity is linked or connected to a particular arena, such as by location, use, affiliation, or operation.
-
D.
board
Indicates that an agent gets onto or into a vehicle, vessel, or craft in order to travel or be transported.
-
E.
belongsToCircuit
Indicates that something is a component or member of a specific circuit or circuit grouping.
- 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4f4fbf481909e4fd7c078b27477 |
completed | March 31, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:11 p.m.