Triple
T25230399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maddale |
E632204
|
entity |
| Predicate | languageRegionAssociation |
P145769
|
FINISHED |
| Object | Kannada cultural region |
—
|
NE NERFINISHED |
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: Kannada cultural region | Statement: [Maddale, languageRegionAssociation, Kannada cultural region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageRegionAssociation Context triple: [Maddale, languageRegionAssociation, Kannada cultural region]
-
A.
subjectLanguageRegion
chosen
Indicates that the subject is associated with or uses a language specific to a particular geographic region.
-
B.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
C.
languageFamilyRegion
Indicates the geographic region or area in which a language family is predominantly found or historically associated.
-
D.
languageRegionsRepresented
Indicates that certain geographic or cultural regions are represented or covered through specific languages.
-
E.
languageArea
Indicates the geographic or cultural region in which a particular language is used or predominantly spoken.
- 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_69e75a8e0f688190a7aebe9a4815e25b |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 21, 2026, 1:04 p.m.