Triple
T28212922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anu Singh |
E711222
|
entity |
| Predicate | caseRaisedIssuesOf |
P29037
|
FINISHED |
| Object | mental health and criminal responsibility |
—
|
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: mental health and criminal responsibility | Statement: [Anu Singh, caseRaisedIssuesOf, mental health and criminal responsibility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseRaisedIssuesOf Context triple: [Anu Singh, caseRaisedIssuesOf, mental health and criminal responsibility]
-
A.
involvesIssue
chosen
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
-
B.
courtIssue
Indicates that a court formally issues or hands down a legal document, order, ruling, or decision to the relevant parties.
-
C.
issueType
Indicates the specific category or classification assigned to an issue within a tracking or management context.
-
D.
raisesIssue
Indicates that one entity brings up, reports, or formally submits a concern, problem, or topic for attention to another entity or system.
-
E.
raisedOn
Indicates that an entity was nurtured, brought up, or spent its formative period in a particular place, environment, or context.
- 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f6434ad2248190a431a5a12c4123d2 |
completed | May 2, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69f63c6c1a948190b68c0f92c264cc0c |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 10:40 p.m.