Triple
T15157122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridges v. California |
E362106
|
entity |
| Predicate | appliesLegalTest |
P113725
|
FINISHED |
| Object | clear and present danger test |
—
|
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: clear and present danger test | Statement: [Bridges v. California, appliesLegalTest, clear and present danger test]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesLegalTest Context triple: [Bridges v. California, appliesLegalTest, clear and present danger test]
-
A.
legalTestType
chosen
Indicates the specific kind or category of legal test or standard that is applied in a given legal context or proceeding.
-
B.
appliesLawThrough
Indicates that one entity enforces, implements, or carries out a law or legal rule by means of another entity or mechanism.
-
C.
legalCodeAppliesTo
Indicates that a particular legal code or statute is applicable to, or governs, a specified subject, situation, or entity.
-
D.
usesLegalCode
Indicates that one entity applies, references, or operates under a particular legal code in its actions or regulations.
-
E.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060c62b08190bcdbd912d011d1ba |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:08 a.m.