Triple

T26037579
Position Surface form Disambiguated ID Type / Status
Subject Ruma Guha Thakurta E647595 entity
Predicate birthName P65 FINISHED
Object Ruma Ghosh
Ruma Ghosh, better known as Ruma Guha Thakurta, was an Indian actress and singer associated with Bengali cinema and music.
E1761994 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: Ruma Ghosh | Statement: [Ruma Guha Thakurta, birthName, Ruma Ghosh]
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: Ruma Ghosh
Triple: [Ruma Guha Thakurta, birthName, Ruma Ghosh]
Generated description
Ruma Ghosh, better known as Ruma Guha Thakurta, was an Indian actress and singer associated with Bengali cinema and music.

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_69e77e8c88f08190858c4c81bd2e1b9a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f6061fd954819082000e723287e423 completed May 2, 2026, 2:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a125354a6a881909a18fe0a917038de completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a12545544f881909f0afd8459986559 completed May 24, 2026, 1:28 a.m.
NED2 Entity disambiguation (via description) batch_6a125879112c8190959380eaef8ccf19 completed May 24, 2026, 1:46 a.m.
Created at: April 22, 2026, 9:08 a.m.