Triple
T23516507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Subordinate Courts of India |
E574381
|
entity |
| Predicate | subjectToReformsIn |
P98268
|
FINISHED |
| Object | case management |
—
|
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: case management | Statement: [Subordinate Courts of India, subjectToReformsIn, case management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectToReformsIn Context triple: [Subordinate Courts of India, subjectToReformsIn, case management]
-
A.
subjectToReformBy
Indicates that an entity is undergoing or designated for changes, improvements, or restructuring carried out by another entity.
-
B.
isPartOfReform
Indicates that an action, measure, or component belongs to, contributes to, or is included within a broader reform initiative or process.
-
C.
reformsBy
Indicates that one entity initiates, implements, or is responsible for changes or improvements (reforms) affecting another entity.
-
D.
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.
-
E.
typeOfReforms
chosen
Indicates the specific kinds or categories of reforms associated with an entity or situation.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1aa82a8448190bf7ad56137c5eb94 |
completed | April 29, 2026, 6:51 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
Created at: April 17, 2026, 6:08 p.m.