Triple

T36928821
Position Surface form Disambiguated ID Type / Status
Subject Neerja E913422 entity
Predicate producer P490 FINISHED
Object Shanti Sivaram Maini
Shanti Sivaram Maini is a film producer best known for producing the acclaimed Hindi biographical thriller "Neerja."
E2216699 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: Shanti Sivaram Maini | Statement: [Neerja, producer, Shanti Sivaram Maini]
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: Shanti Sivaram Maini
Triple: [Neerja, producer, Shanti Sivaram Maini]
Generated description
Shanti Sivaram Maini is a film producer best known for producing the acclaimed Hindi biographical thriller "Neerja."

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_69f76e896c988190880c130e01303dd4 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f9fde3b0f48190aad9b0386384ea79 completed May 5, 2026, 2:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a402b94fd208190ac2e50cf168b4617 completed June 27, 2026, 7:59 p.m.
NEDg Description generation batch_6a402c3a75708190a8e0befbf37865d8 completed June 27, 2026, 8:02 p.m.
NED2 Entity disambiguation (via description) batch_6a402d21ba008190b3036c988c5bcb91 completed June 27, 2026, 8:05 p.m.
Created at: May 3, 2026, 4:13 p.m.