Triple
T3152256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindi Belt |
E65901
|
entity |
| Predicate | languagePolicyImpact |
P22482
|
FINISHED |
| Object | central to debates on Hindi-Urdu and language politics in India |
—
|
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: central to debates on Hindi-Urdu and language politics in India | Statement: [Hindi Belt, languagePolicyImpact, central to debates on Hindi-Urdu and language politics in India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languagePolicyImpact Context triple: [Hindi Belt, languagePolicyImpact, central to debates on Hindi-Urdu and language politics in India]
-
A.
languagePolicyIssue
Indicates that there is a problem, conflict, or concern related to rules or practices governing language use.
-
B.
impactOnLaw
Indicates the effect or influence that one entity, event, or action has on laws, legal rules, or the legal system.
-
C.
legislativeImpact
Indicates the effect that a law or legislative action has on a policy, entity, or outcome.
-
D.
policyLanguage
Indicates the specific wording or formulation used within a policy to express its rules, conditions, or provisions.
-
E.
influencedPolicyArea
chosen
Indicates that one entity has affected, shaped, or guided the development, direction, or implementation of a particular policy area associated with another entity.
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5c27258819099c46a657779780b |
completed | March 8, 2026, 4:37 p.m. |
| PD | Predicate disambiguation | batch_69ad9dfbf0348190952a6bca8fc5fed1 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:05 p.m.