Triple
T17203163
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indiana city courts |
E417529
|
entity |
| Predicate | caseVolumeType |
P10545
|
FINISHED |
| Object | high-volume minor 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: high-volume minor cases | Statement: [Indiana city courts, caseVolumeType, high-volume minor cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseVolumeType Context triple: [Indiana city courts, caseVolumeType, high-volume minor cases]
-
A.
caseTypes
Indicates the types or categories of cases associated with or applicable to an entity or situation.
-
B.
casingType
Indicates the specific kind or category of casing associated with or used by an entity.
-
C.
typicalCaseTypes
chosen
Indicates the kinds or categories of cases that are most commonly associated with or handled by a given entity.
-
D.
caseNumber
Indicates the unique identifying number assigned to a particular legal or administrative case.
-
E.
caseSensitivityVariant
Indicates that one string or textual form is a variant of another that differs only in letter casing (e.g., uppercase vs lowercase).
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42db11fc881908291bf29cc740e09 |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.