Triple
T10213301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rangeela |
E242381
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object |
Rajesh Joshi
Rajesh Joshi is an Indian actor best known for his supporting roles in Hindi films during the 1990s.
|
E860235
|
NE FINISHED |
How this triple was built (4 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: Rajesh Joshi | Statement: [Rangeela, castMember, Rajesh Joshi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rajesh Joshi Context triple: [Rangeela, castMember, Rajesh Joshi]
-
A.
Ramesh Joshi
Ramesh Joshi is a film editor known for his work on the Indian movie "Meghe Dhaka Tara."
-
B.
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.
-
C.
Sanjay Jain
Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
-
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.
Rajeev Samant
Rajeev Samant is an Indian entrepreneur best known as the pioneering founder of Sula Vineyards, one of India’s largest and most influential wine producers.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rajesh Joshi Triple: [Rangeela, castMember, Rajesh Joshi]
Generated description
Rajesh Joshi is an Indian actor best known for his supporting roles in Hindi films during the 1990s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rajesh Joshi Target entity description: Rajesh Joshi is an Indian actor best known for his supporting roles in Hindi films during the 1990s.
-
A.
Ramesh Joshi
Ramesh Joshi is a film editor known for his work on the Indian movie "Meghe Dhaka Tara."
-
B.
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.
-
C.
Sanjay Jain
Sanjay Jain is an economist recognized for his academic contributions and scholarship associated with the Delhi School of Economics.
-
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.
Rajeev Samant
Rajeev Samant is an Indian entrepreneur best known as the pioneering founder of Sula Vineyards, one of India’s largest and most influential wine producers.
- F. None of above. chosen
Provenance (5 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa24efc081909714d98943543283 |
completed | April 6, 2026, 12:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d79490a3c48190a58bff2f63e5873d |
completed | April 9, 2026, 11:59 a.m. |
| NEDg | Description generation | batch_69d79a5c372c8190bdc98efd54d19e13 |
completed | April 9, 2026, 12:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d79af4c5e48190a0f36f689fa5208c |
completed | April 9, 2026, 12:26 p.m. |
Created at: April 6, 2026, 11:03 a.m.