Triple
T11256248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 春の叙勲 |
E266444
|
entity |
| Predicate | 関連制度 |
P32380
|
FINISHED |
| Object | 褒章 |
—
|
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: 褒章 | Statement: [春の叙勲, 関連制度, 褒章]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連制度 Context triple: [春の叙勲, 関連制度, 褒章]
-
A.
関連施設
Indicates a relationship where one facility is associated with, connected to, or otherwise related to another facility.
-
B.
関連主題
Indicates that there exists a thematically or contextually related subject connected to the given entity.
-
C.
relatedRegulation
Indicates that there exists a regulatory rule, law, or directive that is associated with, governs, or is otherwise relevant to the referenced entity or activity.
-
D.
relatedRule
Indicates that one rule is connected or associated with another rule, typically through some logical, structural, or referential relationship.
-
E.
associatedSystem
chosen
Indicates that one entity is functionally or contextually linked to a particular system with which it interacts or to which it belongs.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e935b85c819085e1abf2dd4099c5 |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d78793c00481908a3f764b610b77a4 |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.