Triple
T22394910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabinet Minister of India |
E553603
|
entity |
| Predicate | policyInfluenceLevel |
P9281
|
FINISHED |
| Object | national |
—
|
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: national | Statement: [Cabinet Minister of India, policyInfluenceLevel, national]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyInfluenceLevel Context triple: [Cabinet Minister of India, policyInfluenceLevel, national]
-
A.
influencedPolicyArea
Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
-
B.
typeOfInfluence
Indicates the specific nature or category of influence that one entity exerts on another.
-
C.
pollInfluence
Indicates that one entity affects or shapes the outcome, results, or responses of a poll involving another entity.
-
D.
policyLevel
chosen
Indicates the degree or tier of strictness, scope, or priority associated with a given policy.
-
E.
ruleInfluence
Indicates that one rule affects, constrains, or modifies the behavior, outcome, or applicability of another rule.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585dac3c8190bc221f35b3eefa3f |
completed | April 29, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69e73015484c8190a9a0b9f554b61a81 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:45 p.m.