Triple
T30348935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | エンジェルビーツ |
E771936
|
entity |
| Predicate | メディア展開 |
P161234
|
FINISHED |
| Object | ライトノベル化 |
—
|
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: ライトノベル化 | Statement: [エンジェルビーツ, メディア展開, ライトノベル化]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: メディア展開 Context triple: [エンジェルビーツ, メディア展開, ライトノベル化]
-
A.
メディアミックス
chosen
Indicates that a work or content is being developed, deployed, or promoted across multiple different media formats in a coordinated way.
-
B.
exhibitionMedium
Indicates the material or format through which something is exhibited or displayed.
-
C.
mediaWork
Indicates a relationship where one entity is a media-related work (such as a film, book, recording, or other creative media production) associated with another entity.
-
D.
exhibitFor
Indicates a relationship where something is displayed, presented, or shown for the benefit, use, or consideration of a particular audience, purpose, or entity.
-
E.
mediaExposure
Indicates the extent to which an entity is subjected to or receives attention from media channels such as television, radio, print, or online platforms.
- 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_69f6820a250c8190ba7afa43f6f55c46 |
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.