Triple

T8617340
Position Surface form Disambiguated ID Type / Status
Subject Bhuvan Shome E204072 entity
Predicate editedBy P1954 FINISHED
Object Dipa Sen
Dipa Sen is a film editor known for her work on the landmark Indian film "Bhuvan Shome."
 E745558 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: Dipa Sen | Statement: [Bhuvan Shome, editedBy, Dipa Sen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dipa Sen
Context triple: [Bhuvan Shome, editedBy, Dipa Sen]
  • A. Dipa Nusantara Aidit
    Dipa Nusantara Aidit was an Indonesian communist politician who led the Indonesian Communist Party (PKI) and became a central figure in the political turmoil surrounding the 1965–66 anti-communist purges.
  • B. Pradeep Sindhu
    Pradeep Sindhu is an Indian-American computer scientist and entrepreneur best known as the co-founder and former chief technology officer of networking company Juniper Networks.
  • C. Sandhini Agarwal
    Sandhini Agarwal is an AI researcher known for her work at OpenAI on safety, policy, and the development and deployment of large-scale models such as CLIP.
  • D. Soujanya
    Soujanya is the wife of renowned Indian film director and screenwriter Trivikram Srinivas.
  • E. Shailen Mukherjee
    Shailen Mukherjee was an Indian actor known for his role in Satyajit Ray’s acclaimed Bengali film "Charulata."
  • 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: Dipa Sen
Triple: [Bhuvan Shome, editedBy, Dipa Sen]
Generated description
Dipa Sen is a film editor known for her work on the landmark Indian film "Bhuvan Shome."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dipa Sen
Target entity description: Dipa Sen is a film editor known for her work on the landmark Indian film "Bhuvan Shome."
  • A. Dipa Nusantara Aidit
    Dipa Nusantara Aidit was an Indonesian communist politician who led the Indonesian Communist Party (PKI) and became a central figure in the political turmoil surrounding the 1965–66 anti-communist purges.
  • B. Pradeep Sindhu
    Pradeep Sindhu is an Indian-American computer scientist and entrepreneur best known as the co-founder and former chief technology officer of networking company Juniper Networks.
  • C. Sandhini Agarwal
    Sandhini Agarwal is an AI researcher known for her work at OpenAI on safety, policy, and the development and deployment of large-scale models such as CLIP.
  • D. Soujanya
    Soujanya is the wife of renowned Indian film director and screenwriter Trivikram Srinivas.
  • E. Shailen Mukherjee
    Shailen Mukherjee was an Indian actor known for his role in Satyajit Ray’s acclaimed Bengali film "Charulata."
  • 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_69ca832ceab8819096e4a9f546695079 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc4711c7748190af26ff5a78ef66a2 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea923ae148190a973ef8ad6ccac9a completed April 2, 2026, 5:36 p.m.
NEDg Description generation batch_69cea9d23cc88190b937e89b9aa2bd66 completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaaed65a4819083b6a30baa2c0b97 completed April 2, 2026, 5:44 p.m.
Created at: March 30, 2026, 6:26 p.m.