Triple
T16390673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alabama Court of Criminal Appeals |
E398042
|
entity |
| Predicate | caseTypeReviewed |
P81213
|
FINISHED |
| Object | criminal cases |
—
|
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: criminal cases | Statement: [Alabama Court of Criminal Appeals, caseTypeReviewed, criminal cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseTypeReviewed Context triple: [Alabama Court of Criminal Appeals, caseTypeReviewed, criminal cases]
-
A.
caseTypes
chosen
Indicates the types or categories of cases associated with or applicable to an entity or situation.
-
B.
courtReview
Indicates that a court formally examines a decision, action, or case to determine its legality, correctness, or appropriateness.
-
C.
caseManagement
Indicates that one entity is responsible for coordinating, organizing, and overseeing services or actions provided to another entity within a managed process or case.
-
D.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
-
E.
caseLoad
Indicates the number or collection of cases, tasks, or matters currently assigned to or handled by an entity.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e326425c8081908cacffcfa8c7386b |
completed | April 18, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:08 a.m.