Triple
T14444142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Advisory Committee on Civil Rules |
E358159
|
entity |
| Predicate | typeOfRulemaking |
P95839
|
FINISHED |
| Object | procedural rulemaking |
—
|
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: procedural rulemaking | Statement: [Advisory Committee on Civil Rules, typeOfRulemaking, procedural rulemaking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfRulemaking Context triple: [Advisory Committee on Civil Rules, typeOfRulemaking, procedural rulemaking]
-
A.
regulatoryType
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
-
B.
typeOfRules
chosen
Indicates that one entity specifies or categorizes the kind or category of rules that apply to or are associated with another entity.
-
C.
typeOfRule
Indicates that one rule is classified as a specific kind or category of another, more general rule.
-
D.
typeOfLegislation
Indicates the specific category or kind of legislation that a given legal act or measure belongs to.
-
E.
worksOnRegulationType
Indicates that an entity is involved in work or activities related to a specific type or category of regulation.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de915e76f481909fe9462f964b5b1c |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.