Triple
T29975182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | けんこくきねんのひ |
E761423
|
entity |
| Predicate | 趣旨 |
P26448
|
FINISHED |
| Object | 日本の建国をしのぶ |
—
|
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: 日本の建国をしのぶ | Statement: [けんこくきねんのひ, 趣旨, 日本の建国をしのぶ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 趣旨 Context triple: [けんこくきねんのひ, 趣旨, 日本の建国をしのぶ]
-
A.
culturalInterest
Indicates a relationship where one entity has an interest in, appreciation for, or engagement with the culture, traditions, or cultural expressions associated with another entity.
-
B.
artInterest
Indicates that one entity has an interest in, appreciation for, or engagement with art in relation to another entity or artistic subject.
-
C.
exploresStyle
Indicates that one entity investigates, examines, or experiments with the style or stylistic characteristics of another entity.
-
D.
subjectInterest
Indicates that the subject has an interest in, or is concerned with, the object.
-
E.
featuresTopic
chosen
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
- 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_69f22467626081908d5afea489590e96 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f678d44b848190a0c7887baf01b905 |
completed | May 2, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69f66ec9919881908a187bfc7c4df192 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:33 p.m.