Triple

T27332812
Position Surface form Disambiguated ID Type / Status
Subject Hemanta Mukhopadhyay E689850 entity
Predicate hasChild P369 FINISHED
Object Ranu Mukherjee
Ranu Mukherjee is an Indian playback singer known for her work in Bengali and Hindi cinema, as well as for being the daughter of legendary singer-composer Hemanta Mukhopadhyay.
E1842254 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: Ranu Mukherjee | Statement: [Hemanta Mukhopadhyay, hasChild, Ranu Mukherjee]
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: Ranu Mukherjee
Triple: [Hemanta Mukhopadhyay, hasChild, Ranu Mukherjee]
Generated description
Ranu Mukherjee is an Indian playback singer known for her work in Bengali and Hindi cinema, as well as for being the daughter of legendary singer-composer Hemanta Mukhopadhyay.

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_69ef355e5b388190a8fc1eba9b4a6656 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62acd191481908212829e834fc980 completed May 2, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec14e6388190ba6b15741ad914b8 completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24f07e3a54819090dc0d92cee92204 completed June 7, 2026, 4:15 a.m.
NED2 Entity disambiguation (via description) batch_6a24f56a17a48190a309ea59a2ebf4d1 completed June 7, 2026, 4:36 a.m.
Created at: April 27, 2026, 11:39 a.m.