Triple

T14240171
Position Surface form Disambiguated ID Type / Status
Subject The Boy with the Topknot E352982 entity
Predicate castMember P1668 FINISHED
Object Manpreet Bambra
Manpreet Bambra is a British actress known for her roles in television dramas and teen series, including the BBC adaptation "The Boy with the Topknot."
E1087585 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: Manpreet Bambra | Statement: [The Boy with the Topknot, castMember, Manpreet Bambra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manpreet Bambra
Context triple: [The Boy with the Topknot, castMember, Manpreet Bambra]
  • A. Pawitter Kaur
    Pawitter Kaur was the wife of Giani Zail Singh, the seventh President of India.
  • B. Jesminder "Jess" Bhamra
    Jesminder "Jess" Bhamra is a British-Indian teenager passionate about football who challenges cultural and familial expectations to pursue her dream of playing the sport professionally.
  • C. Simran Singh
    Simran Singh is an entertainment lawyer best known for his former marriage to American actress Jaime Pressly.
  • D. Padmanee Sharma
    Padmanee Sharma is an American oncologist and immunologist known for her pioneering research in cancer immunotherapy and checkpoint blockade.
  • E. Raj Kaur
    Raj Kaur was the mother of Maharaja Ranjit Singh, the founder of the Sikh Empire in the early 19th century.
  • 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: Manpreet Bambra
Triple: [The Boy with the Topknot, castMember, Manpreet Bambra]
Generated description
Manpreet Bambra is a British actress known for her roles in television dramas and teen series, including the BBC adaptation "The Boy with the Topknot."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Manpreet Bambra
Target entity description: Manpreet Bambra is a British actress known for her roles in television dramas and teen series, including the BBC adaptation "The Boy with the Topknot."
  • A. Pawitter Kaur
    Pawitter Kaur was the wife of Giani Zail Singh, the seventh President of India.
  • B. Jesminder "Jess" Bhamra
    Jesminder "Jess" Bhamra is a British-Indian teenager passionate about football who challenges cultural and familial expectations to pursue her dream of playing the sport professionally.
  • C. Simran Singh
    Simran Singh is an entertainment lawyer best known for his former marriage to American actress Jaime Pressly.
  • D. Padmanee Sharma
    Padmanee Sharma is an American oncologist and immunologist known for her pioneering research in cancer immunotherapy and checkpoint blockade.
  • E. Raj Kaur
    Raj Kaur was the mother of Maharaja Ranjit Singh, the founder of the Sikh Empire in the early 19th century.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de62432fb48190b153805b85c4f2d2 completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd282183308190b63172972773b3c2 completed May 8, 2026, 12:02 a.m.
NEDg Description generation batch_69fd29fd7cdc8190bd210f3b27f935c0 completed May 8, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_69fd2bc719ac8190b2b8726c70d811dd completed May 8, 2026, 12:18 a.m.
Created at: April 10, 2026, 1:08 a.m.