Triple

T25255746
Position Surface form Disambiguated ID Type / Status
Subject Kannada cinema E633167 entity
Predicate hasNotableProductionHouse P14415 FINISHED
Object Vajreshwari Combines
Vajreshwari Combines is a prominent film production house in the Kannada-language film industry, known for backing several successful and influential movies.
 E1671862 NE FINISHED

How this triple was built (3 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: Vajreshwari Combines | Statement: [Kannada cinema, hasNotableProductionHouse, Vajreshwari Combines]
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: Vajreshwari Combines
Triple: [Kannada cinema, hasNotableProductionHouse, Vajreshwari Combines]
Generated description
Vajreshwari Combines is a prominent film production house in the Kannada-language film industry, known for backing several successful and influential movies.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasNotableProductionHouse
Context triple: [Kannada cinema, hasNotableProductionHouse, Vajreshwari Combines]
  • A. hasNotableCompany
    Indicates that an entity is associated with or linked to a company that is considered notable or significant in some context.
  • B. hasProduction
    Indicates that an entity is associated with, or responsible for, the creation or manufacture of another entity or product.
  • C. hasProductionCompany chosen
    Indicates that an entity (such as a film, show, or media work) is associated with a specific company responsible for its production.
  • D. hasFictionalProductionCompany
    Indicates that one entity is associated with or owns a production company that exists only within a fictional context.
  • E. ownedProductionCompany
    Indicates that one entity previously possessed ownership or controlling interest in a production company.
  • F. None of above.

Provenance (6 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_69e75a922ad481908f4f1f884583cb42 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f6fb19063c81909466b329655c8583 completed May 3, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067efaf9c81908f825ad8d6426cd5 completed May 22, 2026, 2:27 p.m.
NEDg Description generation batch_6a1068ad981081908f324aa1d7cc5bb2 completed May 22, 2026, 2:31 p.m.
NED2 Entity disambiguation (via description) batch_6a106a170b90819085c5c4dd34966701 completed May 22, 2026, 2:37 p.m.
PD Predicate disambiguation batch_69f6f969b4cc8190afb473a2d8b110bc completed May 3, 2026, 7:29 a.m.
Created at: April 21, 2026, 1:13 p.m.