Triple
T22264524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanaka Dasa |
E550314
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Kanaka Dasa |
—
|
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: Kanaka Dasa | Statement: [Kanaka Dasa, name, Kanaka Dasa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kanaka Dasa Context triple: [Kanaka Dasa, name, Kanaka Dasa]
-
A.
Kanaka Dasa
chosen
Kanaka Dasa was a 16th-century Kannada poet-saint, composer, and social reformer of the Bhakti movement, renowned for his devotional songs and advocacy of equality.
-
B.
Kanakaredes
Kanakaredes is the surname of American actress Melina Kanakaredes, known for her roles on television series such as "CSI: NY" and "Providence."
-
C.
Sankar
Sankar is a common Indian given name and surname, often associated with Hindu cultural and religious traditions.
-
D.
Rukmangada
Rukmangada is a relatively obscure figure in Hindu mythology, known primarily as a son of the sage Jamadagni.
-
E.
Arasuri Ambaji
Arasuri Ambaji is a revered Hindu pilgrimage town in Gujarat, India, centered around the famous Ambaji Temple dedicated to the goddess Amba.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141ba5c9481909e24067133918ae2 |
completed | April 28, 2026, 11:24 p.m. |
Created at: April 16, 2026, 8:39 p.m.