Triple
T28972207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luna |
E734303
|
entity |
| Predicate | hasVideoGameGenreOfWork |
P146635
|
FINISHED |
| Object | Japanese role-playing game |
—
|
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: Japanese role-playing game | Statement: [Luna, hasVideoGameGenreOfWork, Japanese role-playing game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVideoGameGenreOfWork Context triple: [Luna, hasVideoGameGenreOfWork, Japanese role-playing game]
-
A.
hasGenreInVideoGameAdaptations
Indicates that a work is associated with a specific genre specifically in the context of its video game adaptations.
-
B.
hasVideoGames
Indicates that one entity possesses, owns, or includes video games in relation to another entity or context.
-
C.
videoGame
Indicates that one entity is a video game associated with, created by, or otherwise related to another entity.
-
D.
gameGenreDeveloped
Indicates that a particular game genre has been created, defined, or developed by a specific entity (such as a person, team, or organization).
-
E.
hasGenreOfWorkItAppearsIn
chosen
Indicates that an entity is associated with the genre of the work in which it appears.
- 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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: April 28, 2026, 9:06 a.m.