Triple
T20852843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Securitisation Regulation |
E513405
|
entity |
| Predicate | containsRuleType |
P95839
|
FINISHED |
| Object | risk retention rules |
—
|
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: risk retention rules | Statement: [Securitisation Regulation, containsRuleType, risk retention rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsRuleType Context triple: [Securitisation Regulation, containsRuleType, risk retention rules]
-
A.
supportsRuleType
Indicates that one entity is capable of handling, applying, or being compatible with a specified type of rule.
-
B.
hasRule
Indicates that an entity is governed, constrained, or defined by a specific rule or set of rules.
-
C.
hasRuleFor
Indicates that one entity defines or applies a rule that governs or constrains another entity or situation.
-
D.
typeOfRule
Indicates that one rule is classified as a specific kind or category of another, more general rule.
-
E.
typeOfRules
chosen
Indicates that one entity specifies or categorizes the kind or category of rules that apply to or are associated with another entity.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c3a4df5c8190aa0e7684ad6fc9f2 |
completed | April 21, 2026, 12:24 a.m. |
| PD | Predicate disambiguation | batch_69e5c9a593f481908beb457c29f1ce73 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:44 p.m.