Triple
T16997213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chester Crown Court |
E412348
|
entity |
| Predicate | overseesCases |
P31978
|
FINISHED |
| Object | serious criminal cases |
—
|
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: serious criminal cases | Statement: [Chester Crown Court, overseesCases, serious criminal cases]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: overseesCases Context triple: [Chester Crown Court, overseesCases, serious criminal cases]
-
A.
typeOfCasesHandled
chosen
Indicates the categories or kinds of cases that an entity (such as a person, organization, or system) is responsible for managing or processing.
-
B.
hearsCasesAs
Indicates that one judicial body or judge reviews and adjudicates cases originating from another court or jurisdiction.
-
C.
hearsCasesWith
Indicates that one judicial body or judge conducts proceedings together with another judicial body or judge in hearing the same cases.
-
D.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
E.
hearsCasesAgainst
Indicates that one party (typically a judicial body or official) formally listens to and considers legal cases brought against another party.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d2885f888190ab1406f55a91bf93 |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.