Triple
T11555668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judiciary of Ghana |
E274012
|
entity |
| Predicate | appliesLawThrough |
P100294
|
FINISHED |
| Object | court system of Ghana |
—
|
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: court system of Ghana | Statement: [Judiciary of Ghana, appliesLawThrough, court system of Ghana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesLawThrough Context triple: [Judiciary of Ghana, appliesLawThrough, court system of Ghana]
-
A.
appliedLawFrom
Indicates that a specific law or legal provision was applied or derived from a particular source, context, or jurisdiction in a legal decision or situation.
-
B.
legalCodeAppliesTo
Indicates that a particular legal code or statute is applicable to, or governs, a specified subject, situation, or entity.
-
C.
haveLaw
Indicates that a governing body or jurisdiction possesses, enforces, or is characterized by a particular law or set of laws.
-
D.
legalCodeFocus
Indicates that something is specifically concerned with, centered on, or primarily addressing a particular legal code or body of law.
-
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. chosen
Provenance (4 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a86be308190973fea5d7db8ba9d |
completed | April 10, 2026, 5:28 a.m. |
| PD | Predicate disambiguation | batch_69d85dc3fc2c8190bed7e2111301a77c |
completed | April 10, 2026, 2:17 a.m. |
| PDg | Predicate description generation | batch_69d87f2e67108190ac36bf47aac12fa8 |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:37 p.m.