Triple

T28705689
Position Surface form Disambiguated ID Type / Status
Subject Chauranga E729687 entity
Predicate director P255 FINISHED
Object Bikas Ranjan Mishra
Bikas Ranjan Mishra is an Indian filmmaker and screenwriter known for his socially conscious independent cinema.
E2004939 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: Bikas Ranjan Mishra | Statement: [Chauranga, director, Bikas Ranjan Mishra]
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: Bikas Ranjan Mishra
Triple: [Chauranga, director, Bikas Ranjan Mishra]
Generated description
Bikas Ranjan Mishra is an Indian filmmaker and screenwriter known for his socially conscious independent cinema.

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_69f043e6e9688190b6bdd6e5665498ff completed April 28, 2026, 5:21 a.m.
NER Named-entity recognition batch_69f656d333408190aae1211726cefb03 completed May 2, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a344ede1e948190b71b556bc85ba575 completed June 18, 2026, 8:02 p.m.
NEDg Description generation batch_6a344f9edee08190b40cf3f1eb51f8a8 completed June 18, 2026, 8:05 p.m.
NED2 Entity disambiguation (via description) batch_6a34513c68008190829e0525a5a0c9bc completed June 18, 2026, 8:12 p.m.
Created at: April 28, 2026, 5:45 a.m.