Triple
T9314261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crime and Disorder Act 1998 |
E224078
|
entity |
| Predicate | reformsArea |
P88043
|
FINISHED |
| Object | youth justice |
—
|
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: youth justice | Statement: [Crime and Disorder Act 1998, reformsArea, youth justice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reformsArea Context triple: [Crime and Disorder Act 1998, reformsArea, youth justice]
-
A.
reformsBy
Indicates that one entity initiates, implements, or is responsible for changes or improvements (reforms) affecting another entity.
-
B.
relatedReforms
Indicates that one reform is connected or associated with another reform, typically through shared goals, content, or impact.
-
C.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
-
D.
subjectToReformBy
Indicates that an entity is undergoing or designated for changes, improvements, or restructuring carried out by another entity.
-
E.
implementedReformsIn
Indicates that an entity (typically a person, organization, or government) carried out or put into effect specific reforms within a particular context, domain, or location.
- 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.