Triple
T3214937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daijōsai |
E67369
|
entity |
| Predicate | relatedRite |
P37
|
FINISHED |
| Object | enthronement ceremony |
—
|
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: enthronement ceremony | Statement: [Daijōsai, relatedRite, enthronement ceremony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedRite Context triple: [Daijōsai, relatedRite, enthronement ceremony]
-
A.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
B.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
relatedField
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
D.
relatedRFC
Indicates that one resource or specification is connected or associated with another through a shared or relevant RFC (Request for Comments) document.
-
E.
relatedForm
Indicates that one entity is an alternative or variant form of another, such as a different spelling, inflection, or closely related lexical form.
- 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_69ad858ac36c81909962589cd277d6e2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adab085a408190af9fb40acca31a5f |
completed | March 8, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69ad9e09b83881908801d79c3d9254f9 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.