Triple

T10396614
Position Surface form Disambiguated ID Type / Status
Subject Tin Star E245036 entity
Predicate starring P1507 FINISHED
Object Tanya Moodie
Tanya Moodie is a British actress known for her work in television, film, and theatre, including prominent roles in series such as Tin Star and Motherland.
E860477 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: Tanya Moodie | Statement: [Tin Star, starring, Tanya Moodie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanya Moodie
Context triple: [Tin Star, starring, Tanya Moodie]
  • A. Sharyn Mousley
    Sharyn Mousley is the daughter of the late British comedian and television presenter Paul O’Grady.
  • B. Lucinda Edmonds
    Lucinda Edmonds is the birth name of Lucinda Riley, a bestselling Irish author known for her historical and family saga novels, including the "Seven Sisters" series.
  • C. Catherine Moses
    Catherine Moses was the sister of famed American sharpshooter and exhibition shooter Annie Oakley.
  • D. Deborah Milton
    Deborah Milton was the youngest daughter of the English poet John Milton, known primarily through biographical accounts of her father's later life and family.
  • E. Elizabeth Flanagan
    Elizabeth Flanagan was the wife of C. Everett Koop, the prominent U.S. Surgeon General known for his influential public health advocacy.
  • 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: Tanya Moodie
Triple: [Tin Star, starring, Tanya Moodie]
Generated description
Tanya Moodie is a British actress known for her work in television, film, and theatre, including prominent roles in series such as Tin Star and Motherland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tanya Moodie
Target entity description: Tanya Moodie is a British actress known for her work in television, film, and theatre, including prominent roles in series such as Tin Star and Motherland.
  • A. Sharyn Mousley
    Sharyn Mousley is the daughter of the late British comedian and television presenter Paul O’Grady.
  • B. Lucinda Edmonds
    Lucinda Edmonds is the birth name of Lucinda Riley, a bestselling Irish author known for her historical and family saga novels, including the "Seven Sisters" series.
  • C. Catherine Moses
    Catherine Moses was the sister of famed American sharpshooter and exhibition shooter Annie Oakley.
  • D. Deborah Milton
    Deborah Milton was the youngest daughter of the English poet John Milton, known primarily through biographical accounts of her father's later life and family.
  • E. Elizabeth Flanagan
    Elizabeth Flanagan was the wife of C. Everett Koop, the prominent U.S. Surgeon General known for his influential public health advocacy.
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9cf79348190975d6c1791e3b621 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d795cf331c8190b35caf3997dc29a3 completed April 9, 2026, 12:04 p.m.
NEDg Description generation batch_69d7bde050ac8190b87a0c81700ad1b1 completed April 9, 2026, 2:55 p.m.
NED2 Entity disambiguation (via description) batch_69d7e60afaf481909a0790c94e323143 completed April 9, 2026, 5:46 p.m.
Created at: April 6, 2026, 12:06 p.m.