Triple
T6056165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | England and Wales |
E134914
|
entity |
| Predicate | usesLawSystem |
P605
|
FINISHED |
| Object | common law |
—
|
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: common law | Statement: [England and Wales, usesLawSystem, common law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLawSystem Context triple: [England and Wales, usesLawSystem, common law]
-
A.
legalSystemWorkedIn
Indicates that a person carried out their professional legal activities within a particular legal system or jurisdiction.
-
B.
legalSystem
chosen
Indicates the formal framework of laws, rules, and institutions that governs how legal matters are defined, interpreted, and enforced within a society or jurisdiction.
-
C.
legalSystemWorkedOn
Indicates that a legal system has been applied to, influenced, or modified by some agent or process.
-
D.
relatedLegalSystem
Indicates that there is an association or connection between two legal systems, such as influence, similarity, shared origin, or mutual relevance.
-
E.
legalSystemDepictedAs
Indicates that one entity portrays, represents, or characterizes a legal system in a particular way or 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0570bf01c8190a8b2c25b7805d403 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:09 p.m.