Triple
T1409565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South India |
E31773
|
entity |
| Predicate | majorLanguage |
P207
|
FINISHED |
| Object | Kannada |
E8600
|
NE 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: Kannada | Statement: [South India, majorLanguage, Kannada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kannada Context triple: [South India, majorLanguage, Kannada]
-
A.
Kannada
chosen
Kannada is a major Dravidian language predominantly spoken in the Indian state of Karnataka and surrounding regions, with a rich literary tradition spanning over a millennium.
-
B.
Telugu
Telugu is a major Dravidian language predominantly spoken in the Indian states of Andhra Pradesh and Telangana, known for its rich literary tradition and classical status.
-
C.
Tulu
Tulu is a Dravidian language spoken primarily in the coastal regions of Karnataka and northern Kerala in southwestern India, known for its rich oral traditions and distinct cultural identity.
-
D.
Kannada script
The Kannada script is a South Indian abugida primarily used to write the Kannada language, characterized by its rounded letters and shared historical roots with other Brahmic scripts.
-
E.
Hindi
Hindi is an Indo-Aryan language widely spoken across northern and central India and used in government, education, media, and popular culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3c10f44819085e1c4601423740d |
completed | March 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ace578fe4c8190a4d4ced933fac0b6 |
completed | March 8, 2026, 2:56 a.m. |
Created at: March 1, 2026, 7:59 p.m.