Triple
T2323807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Law Division (Circuit Court of Cook County) |
E48239
|
entity |
| Predicate | usesJuries |
P38082
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Law Division (Circuit Court of Cook County), usesJuries, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesJuries Context triple: [Law Division (Circuit Court of Cook County), usesJuries, yes]
-
A.
hasJuryType
Indicates that an entity is associated with, or classified by, a specific type or category of jury.
-
B.
juryProvidedBy
Indicates that a particular jury is supplied, appointed, or made available by a specified source or authority.
-
C.
hasJudge
Indicates that a legal case, proceeding, or decision is presided over or decided by a particular judge.
-
D.
juryComposition
Indicates the relationship specifying how a jury is constituted, including the number, type, or characteristics of its members.
-
E.
usedCourt
Indicates that an entity made use of or participated in legal proceedings within a particular court.
- 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_69a88aa308a88190b0b86c011fda7fce |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc685f05481909c863b29d1f6bacd |
completed | March 7, 2026, 6:32 a.m. |
| PD | Predicate disambiguation | batch_69abc5909cc48190aab257313542dc49 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc682d094819081a96ffb77c4c42a |
completed | March 7, 2026, 6:32 a.m. |
Created at: March 4, 2026, 7:49 p.m.