Triple
T13753875
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talakaveri Wildlife Sanctuary |
E330423
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Talakaveri |
E1014749
|
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: Talakaveri | Statement: [Talakaveri Wildlife Sanctuary, namedAfter, Talakaveri]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Talakaveri Context triple: [Talakaveri Wildlife Sanctuary, namedAfter, Talakaveri]
-
A.
Talakaveri
chosen
Talakaveri is a sacred pilgrimage site in the Brahmagiri Hills of Karnataka, India, revered as the origin of the river Kaveri and home to important Hindu shrines.
-
B.
Bhavani
Bhavani is a fierce and protective form of the Hindu goddess Devi, often associated with power, motherhood, and the destruction of evil.
-
C.
Bhavani
Bhavani is a town in the Erode district of Tamil Nadu, India, known for its location at the confluence of the Bhavani and Cauvery rivers and its prominent temples.
-
D.
Bhavani
Bhavani is a significant river in southern India, known for flowing through Tamil Nadu and contributing majorly to the Kaveri river system.
-
E.
Sadanandavathi
Sadanandavathi was the first wife of Indian actor and politician M. G. Ramachandran.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02179c948190a652cc8c586e418f |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7b06d9fd48190a10b86a0d68fac70 |
completed | May 3, 2026, 8:30 p.m. |
Created at: April 9, 2026, 10:09 p.m.