Triple

T8565343
Position Surface form Disambiguated ID Type / Status
Subject Baashha E202787 entity
Predicate editedBy P1954 FINISHED
Object Ganesh Kumar
Ganesh Kumar is a film editor known for his work on Indian cinema, including editing the popular Tamil film "Baashha."
E746074 NE FINISHED

How this triple was built (4 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: Ganesh Kumar | Statement: [Baashha, editedBy, Ganesh Kumar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ganesh Kumar
Context triple: [Baashha, editedBy, Ganesh Kumar]
  • A. Nirmal Kumar
    Nirmal Kumar was an Indian actor known for his work in Bengali cinema and his marriage to acclaimed actress Madhabi Mukherjee.
  • B. Yogendra Shukla
    Yogendra Shukla was an Indian freedom fighter and revolutionary leader associated with the independence movement against British colonial rule.
  • C. Jagannath Mishra
    Jagannath Mishra was a Bengali Brahmin scholar and the father of the Vaishnava saint and reformer Chaitanya Mahaprabhu.
  • D. Gyanendra Pandey
    Gyanendra Pandey is an Indian historian known for his influential work on nationalism, communalism, and marginalized groups, particularly through his contributions to the Subaltern Studies collective.
  • E. Ashok Chandra
    Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Ganesh Kumar
Triple: [Baashha, editedBy, Ganesh Kumar]
Generated description
Ganesh Kumar is a film editor known for his work on Indian cinema, including editing the popular Tamil film "Baashha."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ganesh Kumar
Target entity description: Ganesh Kumar is a film editor known for his work on Indian cinema, including editing the popular Tamil film "Baashha."
  • A. Nirmal Kumar
    Nirmal Kumar was an Indian actor known for his work in Bengali cinema and his marriage to acclaimed actress Madhabi Mukherjee.
  • B. Yogendra Shukla
    Yogendra Shukla was an Indian freedom fighter and revolutionary leader associated with the independence movement against British colonial rule.
  • C. Jagannath Mishra
    Jagannath Mishra was a Bengali Brahmin scholar and the father of the Vaishnava saint and reformer Chaitanya Mahaprabhu.
  • D. Gyanendra Pandey
    Gyanendra Pandey is an Indian historian known for his influential work on nationalism, communalism, and marginalized groups, particularly through his contributions to the Subaltern Studies collective.
  • E. Ashok Chandra
    Ashok Chandra is a computer scientist known for his contributions to theoretical computer science and complexity theory.
  • F. None of above. chosen

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_69ca8327b0a881908606ff860713964d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe9d2331881909d92ddde90f580e9 completed March 31, 2026, 3:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea87badf081909727808f0e14ae45 completed April 2, 2026, 5:33 p.m.
NEDg Description generation batch_69cea996a5c48190a12ffe8e282d2d9c completed April 2, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_69ceadb2d52c8190aada1d797753663e completed April 2, 2026, 5:56 p.m.
Created at: March 30, 2026, 6:20 p.m.