Triple

T34356585
Position Surface form Disambiguated ID Type / Status
Subject Pankaj Tripathi E881747 entity
Predicate notableWork P4 FINISHED
Object Fukrey Returns
Fukrey Returns is a 2017 Indian Hindi-language comedy film and the sequel to Fukrey, known for its ensemble cast, quirky humor, and continuation of the misadventures of a group of friends in Delhi.
E864213 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: Fukrey Returns | Statement: [Pankaj Tripathi, notableWork, Fukrey Returns]
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: Fukrey Returns
Triple: [Pankaj Tripathi, notableWork, Fukrey Returns]
Generated description
Fukrey Returns is a 2017 Indian Hindi-language comedy film and the sequel to Fukrey, known for its ensemble cast, quirky humor, and continuation of the misadventures of a group of friends in Delhi.

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_69f349bd06008190904c2f86c42749e3 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f71825d88c8190b09c650857684121 completed May 3, 2026, 9:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a370db50c78819091d9d0219e17c0a3 completed June 20, 2026, 10:01 p.m.
NEDg Description generation batch_6a370e995d04819093fe5032b18243ad completed June 20, 2026, 10:05 p.m.
NED2 Entity disambiguation (via description) batch_6a370f63e1d08190a3e588bc7b2fa789 completed June 20, 2026, 10:08 p.m.
Created at: May 1, 2026, 1:58 a.m.