Triple
T25021061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 高天原 |
E626568
|
entity |
| Predicate | 対照的領域 |
P11289
|
FINISHED |
| Object | 混沌や死を象徴する黄泉国と対照される |
—
|
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: 混沌や死を象徴する黄泉国と対照される | Statement: [高天原, 対照的領域, 混沌や死を象徴する黄泉国と対照される]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 対照的領域 Context triple: [高天原, 対照的領域, 混沌や死を象徴する黄泉国と対照される]
-
A.
opposedDomain
Indicates that two domains or areas of activity are in opposition or conflict with each other.
-
B.
contrastedWithBoundary
Indicates a relationship where one entity is compared or set in opposition to a defining limit, edge, or boundary of another entity to highlight their differences.
-
C.
hasAntipodalRegion
Indicates that one region is located at the antipodal position of another region on a sphere, such that each point in one region corresponds to a point directly opposite it in the other.
-
D.
oftenContrastedWith
chosen
Indicates that one entity is frequently compared to another in a way that highlights their differences or opposing characteristics.
-
E.
الضفة
Indicates a spatial relationship where something is located on or associated with a particular bank or side of a river, sea, or similar boundary.
- 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_69e2ff28ee3881909c626af002457a4a |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44ba9d564819087d3b9041bb0205b |
completed | May 1, 2026, 6:43 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:06 a.m.