Triple

T5183424
Position Surface form Disambiguated ID Type / Status
Subject Riya Sen E116972 entity
Predicate spouse P13 FINISHED
Object Shivam Tewari
Shivam Tewari is an Indian photographer known publicly as the husband of actress and model Riya Sen.
 E500757 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: Shivam Tewari | Statement: [Riya Sen, spouse, Shivam Tewari]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Shivam Tewari
Context triple: [Riya Sen, spouse, Shivam Tewari]
  • A. Jaideep Ahlawat
    Jaideep Ahlawat is an Indian actor known for his powerful character roles in films and web series such as "Gangs of Wasseypur," "Raazi," and "Paatal Lok."
  • B. Sachit Mehra
    Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
  • C. Rajat Monga
    Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
  • D. Pranav Shyam
    Pranav Shyam is a computer scientist and AI researcher known for co-authoring influential work in large-scale language models alongside Tom B. Brown and others.
  • E. Suraj Sharma
    Suraj Sharma is an Indian actor best known for his breakout performance as the shipwrecked teenager Pi Patel in Ang Lee’s acclaimed film "Life of Pi."
  • 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: Shivam Tewari
Triple: [Riya Sen, spouse, Shivam Tewari]
Generated description
Shivam Tewari is an Indian photographer known publicly as the husband of actress and model Riya Sen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Shivam Tewari
Target entity description: Shivam Tewari is an Indian photographer known publicly as the husband of actress and model Riya Sen.
  • A. Jaideep Ahlawat
    Jaideep Ahlawat is an Indian actor known for his powerful character roles in films and web series such as "Gangs of Wasseypur," "Raazi," and "Paatal Lok."
  • B. Sachit Mehra
    Sachit Mehra is a Canadian political figure who serves in a top leadership role within the Liberal Party of Canada.
  • C. Rajat Monga
    Rajat Monga is a computer scientist and engineer best known as a co-creator and early lead of TensorFlow at Google Brain.
  • D. Pranav Shyam
    Pranav Shyam is a computer scientist and AI researcher known for co-authoring influential work in large-scale language models alongside Tom B. Brown and others.
  • E. Suraj Sharma
    Suraj Sharma is an Indian actor best known for his breakout performance as the shipwrecked teenager Pi Patel in Ang Lee’s acclaimed film "Life of Pi."
  • 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_69bd446140f08190becb93c61158f27f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd799eb90c8190b738e9478699180f completed March 20, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee0815d848190bacd5ec6a778d91e completed March 21, 2026, 6:16 p.m.
NEDg Description generation batch_69bee58e4c748190bc216bd68c70e863 completed March 21, 2026, 6:38 p.m.
NED2 Entity disambiguation (via description) batch_69bee631b5e081908da0d0ffed1ff6b3 completed March 21, 2026, 6:40 p.m.
Created at: March 20, 2026, 1:46 p.m.