Triple
T27559552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Accountability Ordinance, 1999 |
E695736
|
entity |
| Predicate | typeOfOffencesCovered |
P67290
|
FINISHED |
| Object | public sector corruption |
—
|
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: public sector corruption | Statement: [National Accountability Ordinance, 1999, typeOfOffencesCovered, public sector corruption]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfOffencesCovered Context triple: [National Accountability Ordinance, 1999, typeOfOffencesCovered, public sector corruption]
-
A.
typeOfViolationsCovered
Indicates the kinds or categories of violations that are included within the scope of a rule, policy, agreement, or enforcement action.
-
B.
includesOffenseType
chosen
Indicates that one entity contains, specifies, or is associated with a particular category or type of offense.
-
C.
typeOfOffenseAddressed
Indicates the specific category or kind of offense that a given action, measure, or legal provision is intended to address.
-
D.
appliesToOffencesWithMaximumPenalty
Indicates that the relationship or rule is relevant only to offences whose maximum legal penalty meets a specified threshold or condition.
-
E.
typeOfDiscriminationCovered
Indicates that a particular kind or category of discriminatory behavior is included within the scope of protections, rules, or analysis.
- 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_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fde49a084081909d99b1e0258169d5 |
completed | May 8, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69fde1d04bd881909a46ecbbf18dfe59 |
completed | May 8, 2026, 1:14 p.m. |
Created at: April 27, 2026, 1:38 p.m.