Triple

T15441152
Position Surface form Disambiguated ID Type / Status
Subject Ripper Street E369902 entity
Predicate mainCharacter P1183 FINISHED
Object Long Susan
Long Susan is a central character in the British television drama "Ripper Street," known as a brothel madam navigating the dangers and politics of Victorian London's Whitechapel.
 E1158132 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: Long Susan | Statement: [Ripper Street, mainCharacter, Long Susan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Long Susan
Context triple: [Ripper Street, mainCharacter, Long Susan]
  • A. Suzette
    Suzette is a fictional character appearing in the story or series "The Firefly."
  • B. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • C. 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.
  • D. Suzanne
    Suzanne is a feminine given name of French origin, derived from the Hebrew name Shoshannah meaning “lily.”
  • E. Susie
    Susie is a common diminutive or nickname for the female given name Susanna.
  • 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: Long Susan
Triple: [Ripper Street, mainCharacter, Long Susan]
Generated description
Long Susan is a central character in the British television drama "Ripper Street," known as a brothel madam navigating the dangers and politics of Victorian London's Whitechapel.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Long Susan
Target entity description: Long Susan is a central character in the British television drama "Ripper Street," known as a brothel madam navigating the dangers and politics of Victorian London's Whitechapel.
  • A. Suzette
    Suzette is a fictional character appearing in the story or series "The Firefly."
  • B. Suzanne
    "Suzanne" is a renowned song by Leonard Cohen, celebrated for its poetic lyrics and haunting melody.
  • C. 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.
  • D. Suzanne
    Suzanne is a feminine given name of French origin, derived from the Hebrew name Shoshannah meaning “lily.”
  • E. Susie
    Susie is a common diminutive or nickname for the female given name Susanna.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03eddf258819082679970b7d2b6af completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21a9b9188190a3f5de3ee18c5d3e completed May 9, 2026, 11:59 a.m.
NEDg Description generation batch_69ff22e2f298819085c90e28acafef44 completed May 9, 2026, 12:04 p.m.
NED2 Entity disambiguation (via description) batch_69ff240af68c8190af88834d97a42afb completed May 9, 2026, 12:09 p.m.
Created at: April 10, 2026, 3:21 a.m.