Triple
T36455040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 本栖湖 |
E898127
|
entity |
| Predicate | 関連する作品 |
P185524
|
FINISHED |
| Object | 『湖畔の春』(岡田紅陽の写真)の撮影地 |
—
|
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: 『湖畔の春』(岡田紅陽の写真)の撮影地 | Statement: [本栖湖, 関連する作品, 『湖畔の春』(岡田紅陽の写真)の撮影地]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連する作品 Context triple: [本栖湖, 関連する作品, 『湖畔の春』(岡田紅陽の写真)の撮影地]
-
A.
アニメ作品との関係
Indicates a relationship or association that an entity has with an anime work (e.g., as its creator, character, setting, or related production).
-
B.
relatedToAuthorWork
Indicates that there is a connection or association between an author and a work they have created, contributed to, or are otherwise linked with.
-
C.
starringInRelatedWork
Indicates that an entity appears as a star or lead performer in a work that is related to another primary work or context.
-
D.
hasRelationToOtherWork
Indicates that one work bears a specified relationship (such as adaptation, sequel, reference, or influence) to another distinct work.
-
E.
hasSequelOrRelated
Indicates that one work follows, continues, or is otherwise narratively or thematically related to another work.
- 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_69f76e57f08481908593bd0bc34581c8 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.