Triple

T29334366
Position Surface form Disambiguated ID Type / Status
Subject Naukar Biwi Ka E743869 entity
Predicate writer P1360 FINISHED
Object Brij Katyal
Brij Katyal was an Indian screenwriter known for his work in Hindi cinema, particularly in popular films of the 1960s and 1970s.
E1878015 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: Brij Katyal | Statement: [Naukar Biwi Ka, writer, Brij Katyal]
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: Brij Katyal
Triple: [Naukar Biwi Ka, writer, Brij Katyal]
Generated description
Brij Katyal was an Indian screenwriter known for his work in Hindi cinema, particularly in popular films of the 1960s and 1970s.

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_69f09126cfcc8190899b16fbf3c2bf7b completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f6692112188190982446c3866f66a8 completed May 2, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26614606c08190b745d641d76e6ca8 completed June 8, 2026, 6:29 a.m.
NEDg Description generation batch_6a2672a34d508190b16c656739e97253 completed June 8, 2026, 7:43 a.m.
NED2 Entity disambiguation (via description) batch_6a267663b8708190afe5bc8831d8e929 completed June 8, 2026, 7:59 a.m.
Created at: April 28, 2026, 1:30 p.m.