Triple

T29497237
Position Surface form Disambiguated ID Type / Status
Subject Rajinder Singh Bedi E748265 entity
Predicate notableWork P4 FINISHED
Object Apne Dukh Mujhe De Do
Apne Dukh Mujhe De Do is a renowned collection of short stories in Hindi/Urdu that poignantly explores human suffering and social realities, written by acclaimed writer Rajinder Singh Bedi.
E1869145 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: Apne Dukh Mujhe De Do | Statement: [Rajinder Singh Bedi, notableWork, Apne Dukh Mujhe De Do]
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: Apne Dukh Mujhe De Do
Triple: [Rajinder Singh Bedi, notableWork, Apne Dukh Mujhe De Do]
Generated description
Apne Dukh Mujhe De Do is a renowned collection of short stories in Hindi/Urdu that poignantly explores human suffering and social realities, written by acclaimed writer Rajinder Singh Bedi.

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_69f0bd448c6881908aa6b475cefd5ddc completed April 28, 2026, 1:59 p.m.
NER Named-entity recognition batch_69f66c305c6c819092d8110baaee1ac7 completed May 2, 2026, 9:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25f12d6e5081908ea79bbfa96ac655 completed June 7, 2026, 10:31 p.m.
NEDg Description generation batch_6a25f53de088819084971397f08ca821 completed June 7, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a25f94233508190a175f5e6cb258aff completed June 7, 2026, 11:05 p.m.
Created at: April 28, 2026, 4:20 p.m.