Triple
T10800234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Individual Calendar Section |
E254817
|
entity |
| Predicate | caseAssignmentMethod |
P95539
|
FINISHED |
| Object | each case is assigned to a single judge |
—
|
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: each case is assigned to a single judge | Statement: [Individual Calendar Section, caseAssignmentMethod, each case is assigned to a single judge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseAssignmentMethod Context triple: [Individual Calendar Section, caseAssignmentMethod, each case is assigned to a single judge]
-
A.
requiresAssignment
Indicates that one entity depends on another entity being assigned or allocated before it can proceed, function, or be considered valid.
-
B.
caseTypes
Indicates the types or categories of cases associated with or applicable to an entity or situation.
-
C.
scriptCodeCase
Indicates how the script code is represented with respect to letter casing (e.g., uppercase, lowercase, or mixed case).
-
D.
adoptedByMethod
Indicates that something is accepted, implemented, or brought into use through a specified method or procedure.
-
E.
oneOfCasesIn
Indicates that an entity is one specific member of a defined set or collection of possible cases.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733366c408190bfd3b57be5ef2440 |
completed | April 9, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
| PDg | Predicate description generation | batch_69d6fa334b8c819082eaf8537084c323 |
completed | April 9, 2026, 1 a.m. |
Created at: April 8, 2026, 9:18 p.m.