Triple

T3357878
Position Surface form Disambiguated ID Type / Status
Subject Rachel Brosnahan E70647 entity
Predicate characterPortrayed P1507 FINISHED
Object Susie (The Courier)
Susie is a character from the 2019 spy thriller film "The Courier," portrayed by actress Rachel Brosnahan.
 E350993 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: Susie (The Courier) | Statement: [Rachel Brosnahan, characterPortrayed, Susie (The Courier)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Susie (The Courier)
Context triple: [Rachel Brosnahan, characterPortrayed, Susie (The Courier)]
  • A. Sonya
    Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
  • B. Jeanie
    Jeanie is a female given name, often used as a diminutive of Jean or Jeanne.
  • C. Susy
    Susy is the nickname of Susy Clemens, the daughter of American author Mark Twain.
  • D. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • E. Suzanne
    Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
  • 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: Susie (The Courier)
Triple: [Rachel Brosnahan, characterPortrayed, Susie (The Courier)]
Generated description
Susie is a character from the 2019 spy thriller film "The Courier," portrayed by actress Rachel Brosnahan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Susie (The Courier)
Target entity description: Susie is a character from the 2019 spy thriller film "The Courier," portrayed by actress Rachel Brosnahan.
  • A. Sonya
    Sonya is a gentle, selfless young woman in Leo Tolstoy’s novel "War and Peace," known for her unrequited love and quiet loyalty to the Rostov family.
  • B. Jeanie
    Jeanie is a female given name, often used as a diminutive of Jean or Jeanne.
  • C. Susy
    Susy is the nickname of Susy Clemens, the daughter of American author Mark Twain.
  • D. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • E. Suzanne
    Suzanne is a central character in Steve Martin’s play "Picasso at the Lapin Agile," representing a young woman entangled romantically with both Picasso and other men in the bohemian Parisian setting.
  • 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_69ad85a660c48190998489309a3b4869 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb244435c81908e35d2aa36ec4f46 completed March 8, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3253e91988190bbfdafdf88ab0df1 completed March 12, 2026, 8:42 p.m.
NEDg Description generation batch_69b326cc82788190b68f1db043f21055 completed March 12, 2026, 8:49 p.m.
NED2 Entity disambiguation (via description) batch_69b3276b55a0819094face2e56001921 completed March 12, 2026, 8:51 p.m.
Created at: March 8, 2026, 3:13 p.m.