Triple
T33845059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fadzayi Mahere |
E867456
|
entity |
| Predicate | legalSystemPracticedIn |
P2755
|
FINISHED |
| Object | Zimbabwean 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: Zimbabwean legal system | Statement: [Fadzayi Mahere, legalSystemPracticedIn, Zimbabwean legal system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalSystemPracticedIn Context triple: [Fadzayi Mahere, legalSystemPracticedIn, Zimbabwean legal system]
-
A.
legalSystemWorkedIn
Indicates that a person carried out their professional legal activities within a particular legal system or jurisdiction.
-
B.
legalSystemWorkedOn
Indicates that a legal system has been applied to, influenced, or modified by some agent or process.
-
C.
practicedLawIn
chosen
Indicates that a person engaged in the professional practice of law within a specified jurisdiction or location.
-
D.
usedLegalSystemOf
Indicates that one entity applied, followed, or operated under the legal system or body of laws belonging to another entity.
-
E.
legalSystemRegion
Indicates the geographic or jurisdictional region within which a particular legal system is applicable or in force.
- 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_69f349937b648190a34ada70f6a2b534 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff409ff5548190849c2d50e99bd807 |
completed | May 9, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69ff401a5e188190a72f945e910b4a6c |
completed | May 9, 2026, 2:09 p.m. |
Created at: May 1, 2026, 1:47 a.m.