Triple
T20317062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Second Pension |
E510405
|
entity |
| Predicate | statutoryInstrumentType |
P2588
|
FINISHED |
| Object | social security legislation |
—
|
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: social security legislation | Statement: [State Second Pension, statutoryInstrumentType, social security legislation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: statutoryInstrumentType Context triple: [State Second Pension, statutoryInstrumentType, social security legislation]
-
A.
statutoryType
Indicates the specific legal or statutory category under which something is formally classified or regulated.
-
B.
statutoryScheme
Indicates that one entity is part of, governed by, or defined within a particular statutory or legislative framework.
-
C.
typeOfLegislation
chosen
Indicates the specific category or kind of legislation that a given legal act or measure belongs to.
-
D.
isStatutory
Indicates that something exists, applies, or is defined by virtue of formal law or statute rather than by custom, contract, or other sources.
-
E.
regulatoryType
Indicates the specific kind or category of regulatory control, rule, or oversight that applies in the given relationship.
- 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67788ca3c8190a3496fd54a5870d6 |
completed | April 20, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:19 a.m.