Triple
T26479515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Party Superstars |
E664634
|
entity |
| Predicate | minigamesCount |
P160786
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [Mario Party Superstars, minigamesCount, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minigamesCount Context triple: [Mario Party Superstars, minigamesCount, 100]
-
A.
minigameCountApprox
Indicates that the relationship expresses an approximate or estimated number of minigames associated with an entity.
-
B.
containsMinigame
Indicates that one entity includes or embeds a smaller, self-contained game within it.
-
C.
replacementGamesCount
Indicates the number of substitute or replacement games associated with an event, schedule, or entity.
-
D.
addsMinigames
Indicates that an entity introduces or incorporates additional minigames into another entity, such as a game, system, or platform.
-
E.
minimumNumberOfGames
Indicates the smallest required count of games that must be played or satisfied in a given context or constraint.
- 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_69ee883bc85481909885f92415cbce33 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f612cf14a88190a72376131be70e05 |
completed | May 2, 2026, 3:05 p.m. |
| PD | Predicate disambiguation | batch_69f602d5c8808190a1fdbebd6f0981e8 |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f604120e848190b516c29b781d19cc |
completed | May 2, 2026, 2:02 p.m. |
Created at: April 27, 2026, 12:26 a.m.