Triple
T16964366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulu cinema |
E411505
|
entity |
| Predicate | notableActor |
P7010
|
FINISHED |
| Object |
Arjun Kapikad
Arjun Kapikad is a popular Indian actor best known for his leading roles in contemporary Tulu-language films.
|
E1242546
|
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: Arjun Kapikad | Statement: [Tulu cinema, notableActor, Arjun Kapikad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arjun Kapikad Context triple: [Tulu cinema, notableActor, Arjun Kapikad]
-
A.
Arjun Raina
Arjun Raina is an Indian actor and theatre artist known for his work in film, television, and stage, often associated with experimental and parallel cinema.
-
B.
Ravi Jhankal
Ravi Jhankal is an Indian film, television, and theatre actor known for his character roles in critically acclaimed Hindi productions.
-
C.
Gautam Kumar
Gautam Kumar is known as the son of legendary Indian Bengali actor Uttam Kumar.
-
D.
Kunal Khemu
Kunal Khemu is an Indian film actor who began his career as a popular child artist in the 1990s and later gained recognition for his roles in Hindi comedies and dramas.
-
E.
Arjun Sengupta
Arjun Sengupta was an Indian economist, diplomat, and politician known for his work on human rights, poverty, and the informal economy, including serving as UN Special Rapporteur on the Right to Development.
- 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: Arjun Kapikad Triple: [Tulu cinema, notableActor, Arjun Kapikad]
Generated description
Arjun Kapikad is a popular Indian actor best known for his leading roles in contemporary Tulu-language films.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Arjun Kapikad Target entity description: Arjun Kapikad is a popular Indian actor best known for his leading roles in contemporary Tulu-language films.
-
A.
Arjun Raina
Arjun Raina is an Indian actor and theatre artist known for his work in film, television, and stage, often associated with experimental and parallel cinema.
-
B.
Ravi Jhankal
Ravi Jhankal is an Indian film, television, and theatre actor known for his character roles in critically acclaimed Hindi productions.
-
C.
Gautam Kumar
Gautam Kumar is known as the son of legendary Indian Bengali actor Uttam Kumar.
-
D.
Kunal Khemu
Kunal Khemu is an Indian film actor who began his career as a popular child artist in the 1990s and later gained recognition for his roles in Hindi comedies and dramas.
-
E.
Arjun Sengupta
Arjun Sengupta was an Indian economist, diplomat, and politician known for his work on human rights, poverty, and the informal economy, including serving as UN Special Rapporteur on the Right to Development.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a2cda88190bd574a869f0e43e9 |
completed | April 18, 2026, 6:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d46cb56481908c2bc6648a12fbcf |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d4f1bfa48190903bedc43ed6db75 |
completed | May 10, 2026, 6:56 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d59b96108190a0e55f01529a0b64 |
completed | May 10, 2026, 6:59 p.m. |
Created at: April 10, 2026, 5:31 a.m.