Triple
T29789605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scary But Fun |
E756363
|
entity |
| Predicate | fromVideoGame |
P115844
|
FINISHED |
| Object | Paper Mario: The Thousand-Year Door |
—
|
NE NERFINISHED |
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: Paper Mario: The Thousand-Year Door | Statement: [Scary But Fun, fromVideoGame, Paper Mario: The Thousand-Year Door]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fromVideoGame Context triple: [Scary But Fun, fromVideoGame, Paper Mario: The Thousand-Year Door]
-
A.
videoGame
Indicates that one entity is a video game associated with, created by, or otherwise related to another entity.
-
B.
hasVideoGames
Indicates that one entity possesses, owns, or includes video games in relation to another entity or context.
-
C.
videoGameReputation
Indicates the reputation or standing an entity has within the context of video games, based on how it is perceived, rated, or regarded in that domain.
-
D.
introducedToGame
Indicates that one entity caused or facilitated another entity’s initial exposure or introduction to a particular game.
-
E.
appearedInVideoGame
chosen
Indicates that an entity is featured as a character, element, or content within a specific video game.
- 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f674e137608190af63dfd02ce106ac |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 29, 2026, 5:11 p.m.