Triple
T5857316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marathi theatre |
E130184
|
entity |
| Predicate | hasNotableDirector |
P4744
|
FINISHED |
| Object | Mahesh Elkunchwar |
E603522
|
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: Mahesh Elkunchwar | Statement: [Marathi theatre, hasNotableDirector, Mahesh Elkunchwar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mahesh Elkunchwar Context triple: [Marathi theatre, hasNotableDirector, Mahesh Elkunchwar]
-
A.
Mahesh Elkunchwar
chosen
Mahesh Elkunchwar is a prominent Indian dramatist acclaimed for his innovative and influential contributions to modern Marathi theatre.
-
B.
Umesh Vinayak Kulkarni
Umesh Vinayak Kulkarni is an acclaimed Indian filmmaker known for his critically lauded and genre-defining work in contemporary Marathi cinema.
-
C.
Sunil Sukthankar
Sunil Sukthankar is an acclaimed Indian filmmaker known for his influential work in contemporary Marathi cinema, often focusing on socially relevant and realistic themes.
-
D.
Vijay Joshi
Vijay Joshi is an Indian economist known for his influential work on macroeconomic policy and development, particularly in the context of the Indian economy.
-
E.
Aravind Joshi
Aravind Joshi was an Indian-American computer scientist and computational linguist known for pioneering work in formal grammar formalisms, particularly Tree Adjoining Grammars, and for foundational contributions to natural language processing.
- 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0355755508190ab349cdcf0c8a58d |
completed | March 22, 2026, 6:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70adafa888190be606aba83a50302 |
completed | March 27, 2026, 10:55 p.m. |
Created at: March 22, 2026, 3:56 p.m.