Triple

T4197941
Position Surface form Disambiguated ID Type / Status
Subject Tom Hiddleston E85997 entity
Predicate parent P120 FINISHED
Object Diana Patricia Hiddleston
Diana Patricia Hiddleston is the mother of English actor Tom Hiddleston.
 E431324 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: Diana Patricia Hiddleston | Statement: [Tom Hiddleston, parent, Diana Patricia Hiddleston]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Diana Patricia Hiddleston
Context triple: [Tom Hiddleston, parent, Diana Patricia Hiddleston]
  • A. Emma Hiddleston
    Emma Hiddleston is a British actress and the younger sister of actor Tom Hiddleston.
  • B. Sarah Hiddleston
    Sarah Hiddleston is best known as the sister of British actor Tom Hiddleston.
  • C. Saskia Reeves
    Saskia Reeves is a British actress known for her work in film, television, and theatre, including roles in series such as "Luther" and numerous acclaimed stage productions.
  • D. Emma Watson
    Emma Watson is a British actress and activist best known for playing Hermione Granger in the Harry Potter film series and for her advocacy on gender equality.
  • E. Sienna Miller
    Sienna Miller is a British-American actress and model known for her roles in films such as "Layer Cake," "Factory Girl," and "American Sniper," as well as for her prominent presence in 2000s popular culture and fashion.
  • 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: Diana Patricia Hiddleston
Triple: [Tom Hiddleston, parent, Diana Patricia Hiddleston]
Generated description
Diana Patricia Hiddleston is the mother of English actor Tom Hiddleston.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Diana Patricia Hiddleston
Target entity description: Diana Patricia Hiddleston is the mother of English actor Tom Hiddleston.
  • A. Emma Hiddleston
    Emma Hiddleston is a British actress and the younger sister of actor Tom Hiddleston.
  • B. Sarah Hiddleston
    Sarah Hiddleston is best known as the sister of British actor Tom Hiddleston.
  • C. Saskia Reeves
    Saskia Reeves is a British actress known for her work in film, television, and theatre, including roles in series such as "Luther" and numerous acclaimed stage productions.
  • D. Emma Watson
    Emma Watson is a British actress and activist best known for playing Hermione Granger in the Harry Potter film series and for her advocacy on gender equality.
  • E. Sienna Miller
    Sienna Miller is a British-American actress and model known for her roles in films such as "Layer Cake," "Factory Girl," and "American Sniper," as well as for her prominent presence in 2000s popular culture and fashion.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0360bc8081908ceb2483eef89174 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d05b964881908d7d52b70cec2dcc completed March 14, 2026, 9:17 p.m.
NEDg Description generation batch_69b5d24c25088190b002aa4231d5f5c4 completed March 14, 2026, 9:25 p.m.
NED2 Entity disambiguation (via description) batch_69b5d2c040a081909c74d1a6cbf54dd6 completed March 14, 2026, 9:27 p.m.
Created at: March 9, 2026, 3:48 p.m.