Triple
T6254523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varanasi (Lok Sabha constituency) |
E140127
|
entity |
| Predicate | otherMajorLanguage |
P12203
|
FINISHED |
| Object | Bhojpuri |
—
|
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: Bhojpuri | Statement: [Varanasi (Lok Sabha constituency), otherMajorLanguage, Bhojpuri]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: otherMajorLanguage Context triple: [Varanasi (Lok Sabha constituency), otherMajorLanguage, Bhojpuri]
-
A.
otherLanguage
chosen
Indicates that an entity has or uses an additional language distinct from its primary or main language.
-
B.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
-
C.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
D.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
E.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
- 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_69c008b4858c819095b0199114a9a87b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063625608819081f5422112c80ce5 |
completed | March 22, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69c05605566c81908e197f5accd072d2 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:24 p.m.