Triple

T10453298
Position Surface form Disambiguated ID Type / Status
Subject Thomas Brodie-Sangster E246487 entity
Predicate familyName P18 FINISHED
Object Sangster
Sangster is the surname of English actor Thomas Brodie-Sangster, known for roles in films like "Love Actually" and series such as "Game of Thrones" and "The Queen's Gambit."
 E863486 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: Sangster | Statement: [Thomas Brodie-Sangster, familyName, Sangster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sangster
Context triple: [Thomas Brodie-Sangster, familyName, Sangster]
  • A. Carricart
    Carricart is a Spanish-language surname of likely Basque origin borne by individuals such as María del Carmen Cerruti Carricart.
  • B. Gonsalves
    Gonsalves is a Portuguese-origin surname commonly found in Lusophone and Caribbean communities.
  • C. Abataranika
    Abataranika is a Bengali literary work that served as the source material for the film "Mahanagar."
  • D. Talibra
    Talibra is an independent music label associated with the release of Talib Kweli’s album "Gutter Rainbows."
  • E. Angleton
    Angleton is the surname most notably associated with James Jesus Angleton, the influential and controversial chief of counterintelligence for the U.S. Central Intelligence Agency during the Cold War.
  • 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: Sangster
Triple: [Thomas Brodie-Sangster, familyName, Sangster]
Generated description
Sangster is the surname of English actor Thomas Brodie-Sangster, known for roles in films like "Love Actually" and series such as "Game of Thrones" and "The Queen's Gambit."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sangster
Target entity description: Sangster is the surname of English actor Thomas Brodie-Sangster, known for roles in films like "Love Actually" and series such as "Game of Thrones" and "The Queen's Gambit."
  • A. Carricart
    Carricart is a Spanish-language surname of likely Basque origin borne by individuals such as María del Carmen Cerruti Carricart.
  • B. Gonsalves
    Gonsalves is a Portuguese-origin surname commonly found in Lusophone and Caribbean communities.
  • C. Abataranika
    Abataranika is a Bengali literary work that served as the source material for the film "Mahanagar."
  • D. Talibra
    Talibra is an independent music label associated with the release of Talib Kweli’s album "Gutter Rainbows."
  • E. Angleton
    Angleton is the surname most notably associated with James Jesus Angleton, the influential and controversial chief of counterintelligence for the U.S. Central Intelligence Agency during the Cold War.
  • 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_69d381c04fe08190957c26c526a3b05a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fe0d73d48190acb687b96918e0cf completed April 7, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69d87f07c9f48190b0fce7740a2e003a completed April 10, 2026, 4:39 a.m.
NEDg Description generation batch_69d886c562c081908aae846da8efb1a5 completed April 10, 2026, 5:12 a.m.
NED2 Entity disambiguation (via description) batch_69d88dce21448190b093b4f548e29f84 completed April 10, 2026, 5:42 a.m.
Created at: April 6, 2026, 12:17 p.m.