Triple
T26692925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Party: The Top 100 |
E672936
|
entity |
| Predicate | hasBoardGameplay |
P171408
|
FINISHED |
| Object | limited compared to mainline Mario Party titles |
—
|
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: limited compared to mainline Mario Party titles | Statement: [Mario Party: The Top 100, hasBoardGameplay, limited compared to mainline Mario Party titles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardGameplay Context triple: [Mario Party: The Top 100, hasBoardGameplay, limited compared to mainline Mario Party titles]
-
A.
hasGamesAt
Indicates that a particular location, venue, or platform hosts or offers one or more games.
-
B.
boardGameGeekCategory
Indicates that something is classified under a specific category in the BoardGameGeek taxonomy of board game types or themes.
-
C.
hasBeenPlayedIn
Indicates that an entity (such as a song, video, or game) has been previously played or performed within a particular context or medium.
-
D.
playedWith
Indicates that one entity engaged in play or a playful activity together with another entity.
-
E.
board
Indicates that an agent gets onto or into a vehicle, vessel, or craft in order to travel or be transported.
- 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_69eecda2066c8190a344218afa5e89c1 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f69f80b62c8190bf2af2be0d3a7df8 |
completed | May 3, 2026, 1:06 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
| PDg | Predicate description generation | batch_69f69edae2448190925ce701c8792c52 |
completed | May 3, 2026, 1:03 a.m. |
Created at: April 27, 2026, 3:27 a.m.