Triple
T3201409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frazee v. Illinois Department of Employment Security |
E67059
|
entity |
| Predicate | decisionCategory |
P2165
|
FINISHED |
| Object | religious liberty decision |
—
|
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: religious liberty decision | Statement: [Frazee v. Illinois Department of Employment Security, decisionCategory, religious liberty decision]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decisionCategory Context triple: [Frazee v. Illinois Department of Employment Security, decisionCategory, religious liberty decision]
-
A.
decisionType
chosen
Indicates the specific category or nature of a decision associated with an entity or event.
-
B.
decisionMaking
Indicates the process by which an entity evaluates options and selects a course of action among alternatives.
-
C.
decisionLanguage
Indicates that a decision, statement, or choice is expressed or recorded in a particular natural language.
-
D.
decisionScope
Indicates the range or domain within which a particular decision is valid, applicable, or has authority.
-
E.
decisionEffect
Indicates that one decision leads to, influences, or determines a particular outcome or consequence.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9aedef08190824bdf508f85f06f |
completed | March 8, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69ad9e078f7c8190813d9fcb4f5071fb |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.