Triple
T9314175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Criminal Justice Act 1967 |
E224076
|
entity |
| Predicate | affectedAdministrationOfJustice |
P88038
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Criminal Justice Act 1967, affectedAdministrationOfJustice, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedAdministrationOfJustice Context triple: [Criminal Justice Act 1967, affectedAdministrationOfJustice, yes]
-
A.
affectedCourt
Indicates that a particular court is impacted or influenced by a specified action, decision, or legal matter.
-
B.
affectedJurisdictionOver
Indicates that one entity’s authority, control, or legal power extends over and impacts the jurisdiction of another entity.
-
C.
hasJurisdictionalConsequence
Indicates that an action, decision, or fact results in a legal or administrative effect within a particular jurisdiction or authority.
-
D.
affectsStatute
Indicates that one legal action, decision, or document has a modifying, influencing, or changing impact on a particular statute.
-
E.
impactOnCaseFlow
Indicates how an event, action, or decision affects the progression, timing, or movement of cases through a process or system.
- 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_69ca8425f4fc81909c1c586e9a5b7530 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd20b2274481908ddb4eda70cea8cc |
completed | April 1, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:37 p.m.