Triple
T5905141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 皇居 |
E131323
|
entity |
| Predicate | 関連法令 |
P3136
|
FINISHED |
| Object | 皇室経済法 |
—
|
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: 皇室経済法 | Statement: [皇居, 関連法令, 皇室経済法]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 関連法令 Context triple: [皇居, 関連法令, 皇室経済法]
-
A.
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.
-
B.
relatedLegislation
chosen
Indicates that there exists a legislative document that is connected to, affects, or is otherwise relevant to the subject entity.
-
C.
relatedLegalConcept
Indicates that one legal concept is connected or associated with another through a relevant legal relationship or context.
-
D.
containsLawOn
Indicates that one entity (such as a document, code, or regulation) includes or sets forth legal provisions concerning another entity or subject.
-
E.
relatedLegalSystem
Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
- 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_69c0085864a88190a569c05ff7d65f29 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0334fcf6481908e8e74105de9d49b |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.