Triple
T29399002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 大伴旅人 |
E745582
|
entity |
| Predicate | 関与した作品 |
P74692
|
FINISHED |
| Object | 『万葉集』 |
—
|
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: 『万葉集』 | Statement: [大伴旅人, 関与した作品, 『万葉集』]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関与した作品 Context triple: [大伴旅人, 関与した作品, 『万葉集』]
-
A.
starringInRelatedWork
Indicates that an entity appears as a star or lead performer in a work that is related to another primary work or context.
-
B.
hasBeenInvolvedIn
chosen
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
-
C.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
-
D.
associatedWithWorkOf
Indicates that one entity has a connection or involvement with the work, creation, or output produced by another entity.
-
E.
hasRelationToOtherWork
Indicates that one work bears a specified relationship (such as adaptation, sequel, reference, or influence) to another distinct work.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66a055e9c8190b8e779d7f75eafa2 |
completed | May 2, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69f660f4f7a88190b93c60d76b86c912 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 2:49 p.m.