Triple
T1978610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yao City government |
E42972
|
entity |
| Predicate | operatesWithinLegalFrameworkOf |
P12605
|
FINISHED |
| Object | laws of Japan |
—
|
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: laws of Japan | Statement: [Yao City government, operatesWithinLegalFrameworkOf, laws of Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesWithinLegalFrameworkOf Context triple: [Yao City government, operatesWithinLegalFrameworkOf, laws of Japan]
-
A.
operatesWithin
Indicates that one entity carries out its activities, functions, or operations inside the scope, boundaries, or jurisdiction defined by another entity.
-
B.
governedByLegalRegime
chosen
Indicates that an entity is subject to, regulated by, or operating under a specific legal framework or set of legal rules.
-
C.
givesLegalOpinionTo
Indicates that one party provides a formal legal judgment, advice, or interpretation to another party.
-
D.
usesLegalCode
Indicates that one entity applies, references, or operates under a particular legal code in its actions or regulations.
-
E.
containsLawOn
Indicates that one entity (such as a document, code, or regulation) includes or sets forth legal provisions concerning another entity or subject.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb43011188190b6a41c004e9e4802 |
completed | March 7, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_69abaff9a09c8190a81fa13f4b85bc79 |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.