Triple
T31056341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sex Offender Order |
E791407
|
entity |
| Predicate | breachConsequences |
P36372
|
FINISHED |
| Object | criminal offence |
—
|
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: criminal offence | Statement: [Sex Offender Order, breachConsequences, criminal offence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: breachConsequences Context triple: [Sex Offender Order, breachConsequences, criminal offence]
-
A.
violationConsequences
chosen
Indicates the negative outcomes, penalties, or repercussions that result from a violation of a rule, law, or agreement.
-
B.
riskIfBreached
Indicates that a breach of the referenced entity or condition would expose or create a potential risk or harm.
-
C.
ruptureConsequence
Indicates the resulting state, effect, or outcome that follows from a rupture event.
-
D.
breachedDuring
Indicates that one entity violated, broke, or failed to uphold another entity (such as a rule, contract, or security measure) within a specified time period or event.
-
E.
exploresConsequencesOf
Indicates that one entity investigates, analyzes, or examines the outcomes, implications, or effects resulting from another entity or event.
- 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_69f224cb08908190ba71ad9aa87518ed |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f695441b3c8190943f67a89e070329 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690f13d7481908ddfefe95df2a1c2 |
completed | May 3, 2026, 12:04 a.m. |
Created at: April 29, 2026, 9 p.m.