Triple

T27166312
Position Surface form Disambiguated ID Type / Status
Subject Deewana E682788 entity
Predicate producer P490 FINISHED
Object Guddu Dhanoa
Guddu Dhanoa is an Indian film producer and director known for his work in Hindi cinema, particularly in the action and drama genres.
E1762110 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: Guddu Dhanoa | Statement: [Deewana, producer, Guddu Dhanoa]
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: Guddu Dhanoa
Triple: [Deewana, producer, Guddu Dhanoa]
Generated description
Guddu Dhanoa is an Indian film producer and director known for his work in Hindi cinema, particularly in the action and drama genres.

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_69eefacf6e788190a75a64399d9e3109 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6254313508190a1946b5c58f6dd3b completed May 2, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1253853b648190a75e7a57181f5e9b completed May 24, 2026, 1:25 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 27, 2026, 9:21 a.m.