Triple

T30234155
Position Surface form Disambiguated ID Type / Status
Subject Prakash Raj E768711 entity
Predicate directed P7373 FINISHED
Object Naanu Nanna Kanasu
Naanu Nanna Kanasu is a Kannada-language drama film known for its emotional portrayal of a father-daughter relationship, featuring and directed by acclaimed actor-filmmaker Prakash Raj.
E1905022 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: Naanu Nanna Kanasu | Statement: [Prakash Raj, directed, Naanu Nanna Kanasu]
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: Naanu Nanna Kanasu
Triple: [Prakash Raj, directed, Naanu Nanna Kanasu]
Generated description
Naanu Nanna Kanasu is a Kannada-language drama film known for its emotional portrayal of a father-daughter relationship, featuring and directed by acclaimed actor-filmmaker Prakash Raj.

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_69f224820c048190b1435c4cc145acf1 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68048f7e481908c7b6e3788b04549 completed May 2, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27644929288190a30edfe721aec40a completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a2764dcc7148190b7ba48ce073f845f completed June 9, 2026, 12:57 a.m.
NED2 Entity disambiguation (via description) batch_6a2765db45d88190817f04133b5efd75 completed June 9, 2026, 1:01 a.m.
Created at: April 29, 2026, 7:37 p.m.