Triple

T27330441
Position Surface form Disambiguated ID Type / Status
Subject Salil Chowdhury E689783 entity
Predicate name P16 FINISHED
Object Salil Choudhury
Salil Choudhury was a renowned Indian music composer, lyricist, and writer known for his influential work in Bengali and Hindi cinema and his integration of folk and Western musical elements.
E1945840 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: Salil Choudhury | Statement: [Salil Chowdhury, name, Salil Choudhury]
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: Salil Choudhury
Triple: [Salil Chowdhury, name, Salil Choudhury]
Generated description
Salil Choudhury was a renowned Indian music composer, lyricist, and writer known for his influential work in Bengali and Hindi cinema and his integration of folk and Western musical elements.

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_69ef355d4cb08190ab032c0a2e7d3753 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62acb65fc8190848dbe87124811ae completed May 2, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a292ae605148190936d8e9762c6d2f6 completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292f17b0d88190a8127db7fef88d4a completed June 10, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_6a29336ad4a88190913d094aaa393fcf completed June 10, 2026, 9:50 a.m.
Created at: April 27, 2026, 11:37 a.m.