Triple
T658662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi English |
E11704
|
entity |
| Predicate | regionSpecificVocabularyFrom |
P1762
|
FINISHED |
| Object | Delhi Hindi slang |
—
|
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: Delhi Hindi slang | Statement: [Delhi English, regionSpecificVocabularyFrom, Delhi Hindi slang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionSpecificVocabularyFrom Context triple: [Delhi English, regionSpecificVocabularyFrom, Delhi Hindi slang]
-
A.
regionSpecificContent
Indicates that certain content is tailored, restricted, or applicable only to a particular geographic region or set of regions.
-
B.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
C.
regionalVariantOf
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
-
D.
regionalDialect
chosen
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
E.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0f55f7481909e052a25bd12d455 |
completed | March 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69a49d1406ec8190abf546549264c85d |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.