Triple
T30349983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fate/Grand Order |
E771965
|
entity |
| Predicate | scenarioWriter |
P53375
|
FINISHED |
| Object | Kinoko Nasu |
—
|
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: Kinoko Nasu | Statement: [Fate/Grand Order, scenarioWriter, Kinoko Nasu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scenarioWriter Context triple: [Fate/Grand Order, scenarioWriter, Kinoko Nasu]
-
A.
narrativeDesigner
Indicates a relationship where an entity serves as the creator or architect of a story’s structure, dialogue, and interactive narrative elements for another entity such as a game, experience, or project.
-
B.
storyEngine
Indicates that one entity functions as a narrative-generating or plot-controlling mechanism for another entity or set of events.
-
C.
scriptWriter
chosen
Indicates that one entity is the person who wrote or authored the script associated with another entity.
-
D.
scenarioType
Indicates the specific category or kind of situation, context, or use case that an entity or event is associated with.
-
E.
dialogueWriter
Indicates that an entity is responsible for writing or creating dialogue for another entity, work, or context.
- 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_69f2248b9a208190bc3e6804acd5afd6 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6820b4b8c81908f5bbae956565ec0 |
completed | May 2, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69f678d019fc8190913662cd2f87b857 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:56 p.m.