Triple
T26582261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronald H. Bradley |
E667108
|
entity |
| Predicate | associatedLegalTopic |
P61922
|
FINISHED |
| Object | remedial powers of federal courts |
—
|
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: remedial powers of federal courts | Statement: [Ronald H. Bradley, associatedLegalTopic, remedial powers of federal courts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedLegalTopic Context triple: [Ronald H. Bradley, associatedLegalTopic, remedial powers of federal courts]
-
A.
relatedLegalConcept
chosen
Indicates that one legal concept is connected or associated with another through a relevant legal relationship or context.
-
B.
legalMatters
Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
-
C.
subjectOfLaw
Indicates that a law, legal document, or legal provision is about, concerns, or applies to the referenced subject.
-
D.
legalSubject
Indicates that an entity is the bearer of legal rights, duties, or responsibilities within a legal relationship or context.
-
E.
mainLegalIssue
Indicates the primary legal question or dispute that is central to a case or legal matter.
- 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_69ee9cfb7e548190b60a9031182f5a7e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69ff46afe7e481908f2862ed11c88db2 |
completed | May 9, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69ff45e9151881909c444a655e852165 |
completed | May 9, 2026, 2:34 p.m. |
Created at: April 27, 2026, 2:03 a.m.