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.