Triple
T5489438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanyadaan |
E123663
|
entity |
| Predicate | protagonist |
P268
|
FINISHED |
| Object | Jyoti Devlalikar |
E524882
|
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: Jyoti Devlalikar | Statement: [Kanyadaan, protagonist, Jyoti Devlalikar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jyoti Devlalikar Context triple: [Kanyadaan, protagonist, Jyoti Devlalikar]
-
A.
Jyoti Devlalikar
chosen
Jyoti Devlalikar is a character in the Indian television series "Kanyadaan."
-
B.
Jyoti Bansal
Jyoti Bansal is an Indian-American entrepreneur and technologist best known for founding the application performance management company AppDynamics, which was acquired by Cisco for billions of dollars.
-
C.
Nath Devlalikar
Nath Devlalikar is a central male character in Vijay Tendulkar’s Marathi play "Kanyadaan," representing liberal idealism and its clash with harsh social realities.
-
D.
Manikarnika Tambe
Manikarnika Tambe was the birth name of Rani Lakshmibai of Jhansi, a leading queen and warrior of the Indian Rebellion of 1857.
-
E.
Sumedha Kailash
Sumedha Kailash is an Indian child rights activist known for her work alongside her husband, Nobel laureate Kailash Satyarthi, in rescuing and rehabilitating bonded and exploited children.
- 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_69bd464a2d908190869324ce176779c8 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927dcb848190a9d31e2435f8a755 |
completed | March 20, 2026, 6:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf833b88d881908e9b6180c74f72fb |
completed | March 22, 2026, 5:50 a.m. |
Created at: March 20, 2026, 2:10 p.m.