Triple
T18040741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crime and Courts Act 2013 |
E431643
|
entity |
| Predicate | part3Title |
P33752
|
FINISHED |
| Object | Miscellaneous and General |
—
|
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: Miscellaneous and General | Statement: [Crime and Courts Act 2013, part3Title, Miscellaneous and General]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: part3Title Context triple: [Crime and Courts Act 2013, part3Title, Miscellaneous and General]
-
A.
thirdPartTitle
chosen
Indicates that an entity holds the title or designation of the third part in a sequence, series, or multipart structure.
-
B.
fourthPartTitle
Indicates that the specified title is the fourth part in a sequence or multi-part work.
-
C.
secondPartTitle
Indicates that one entity is the second part of the title of another entity.
-
D.
part2Content
Indicates that something constitutes the second part or segment of a larger piece of content.
-
E.
titleOfPart
Indicates that one entity is the title specifically assigned to a part or section of another, larger work or resource.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bfee78048190b3fada0eb3d28c77 |
completed | April 19, 2026, 11:43 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
Created at: April 10, 2026, 10:25 a.m.