Triple
T18470109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UK Bribery Act 2010 |
E451272
|
entity |
| Predicate | maximumPenaltyForIndividuals |
P131772
|
FINISHED |
| Object | 10 years imprisonment |
—
|
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: 10 years imprisonment | Statement: [UK Bribery Act 2010, maximumPenaltyForIndividuals, 10 years imprisonment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumPenaltyForIndividuals Context triple: [UK Bribery Act 2010, maximumPenaltyForIndividuals, 10 years imprisonment]
-
A.
maximumPenaltySection1
Indicates the legal provision that specifies the highest penalty allowed under section 1 of a statute or regulation.
-
B.
numberOfPeoplePunished
Indicates the count of individuals who received punishment in relation to a specified event, action, or context.
-
C.
penaltyPoints
Indicates that a certain number of negative points or demerits are assigned to an entity as a consequence of a rule violation, error, or infraction.
-
D.
defaultPenalty
Indicates that a standard or automatically applied penalty is imposed in the absence of a specific or overridden penalty.
-
E.
penaltyRules
Indicates the rules or conditions under which penalties are defined, applied, or enforced in a given context.
- F. None of above. chosen
Provenance (4 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_69d8d38465a0819099b9b42d2a662ac1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5305e349c8190925166bc3dddb320 |
completed | April 19, 2026, 7:43 p.m. |
| PD | Predicate disambiguation | batch_69e469d05cf4819099baf1665a9cf18a |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2aa72c8190a40854a7a52081e2 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:34 a.m.