Triple

T566198
Position Surface form Disambiguated ID Type / Status
Subject The Master E13557 entity
Predicate portrayedBy P1507 FINISHED
Object Sacha Dhawan
Sacha Dhawan is a British actor known for his versatile television and film roles, including his acclaimed portrayal of the Master in the long-running sci-fi series Doctor Who.
E71113 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: Sacha Dhawan | Statement: [The Master, portrayedBy, Sacha Dhawan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sacha Dhawan
Context triple: [The Master, portrayedBy, Sacha Dhawan]
  • A. Dev Patel
    Dev Patel is a British actor known for his breakout role in "Slumdog Millionaire" and acclaimed performances in films such as "Lion" and "The Green Knight."
  • B. Salman
    Salman is the given name of Salman Rushdie, the renowned British-Indian novelist known for works such as "Midnight's Children" and "The Satanic Verses."
  • 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. Naveen Andrews
    Naveen Andrews is a British actor best known for his roles in the television series "Lost" and films such as "The English Patient."
  • E. Deepak Kapur
    Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
  • 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: Sacha Dhawan
Triple: [The Master, portrayedBy, Sacha Dhawan]
Generated description
Sacha Dhawan is a British actor known for his versatile television and film roles, including his acclaimed portrayal of the Master in the long-running sci-fi series Doctor Who.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sacha Dhawan
Target entity description: Sacha Dhawan is a British actor known for his versatile television and film roles, including his acclaimed portrayal of the Master in the long-running sci-fi series Doctor Who.
  • A. Dev Patel
    Dev Patel is a British actor known for his breakout role in "Slumdog Millionaire" and acclaimed performances in films such as "Lion" and "The Green Knight."
  • B. Salman
    Salman is the given name of Salman Rushdie, the renowned British-Indian novelist known for works such as "Midnight's Children" and "The Satanic Verses."
  • 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. Naveen Andrews
    Naveen Andrews is a British actor best known for his roles in the television series "Lost" and films such as "The English Patient."
  • E. Deepak Kapur
    Deepak Kapur is a computer scientist known for his influential work in automated reasoning and term rewriting systems.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b01aca48190944408d066519149 completed March 1, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4efd0d5b88190a8c0822800f48e2a completed March 2, 2026, 2:02 a.m.
NEDg Description generation batch_69a4f043efec8190a3f53ab2764252be completed March 2, 2026, 2:04 a.m.
NED2 Entity disambiguation (via description) batch_69a4f3eb1e3481909aa2b8290ed99e49 completed March 2, 2026, 2:20 a.m.
Created at: March 1, 2026, 7:32 p.m.