Triple
T12280078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stake Bay |
E292693
|
entity |
| Predicate | hasLegalSystemOf |
P16986
|
FINISHED |
| Object | Cayman Islands legal system |
—
|
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: Cayman Islands legal system | Statement: [Stake Bay, hasLegalSystemOf, Cayman Islands legal system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalSystemOf Context triple: [Stake Bay, hasLegalSystemOf, Cayman Islands legal system]
-
A.
countryOfLegalSystem
Indicates the relationship between a legal system and the country in which that legal system is officially established or applied.
-
B.
hasLegalSystemType
Indicates that an entity possesses or is governed by a particular type or form of legal system.
-
C.
hasExtendedLawSystem
Indicates that an entity possesses a comprehensive, detailed, and well-developed system of laws or legal regulations.
-
D.
legalSystemRegion
Indicates the geographic or jurisdictional region within which a particular legal system is applicable or in force.
-
E.
relatedLegalSystem
chosen
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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.