Triple

T20161934
Position Surface form Disambiguated ID Type / Status
Subject The Red Mill E491727 entity
Predicate hasCharacter P2308 FINISHED
Object Berta
Berta is a fictional character from the operetta "The Red Mill," likely serving as one of its supporting comedic or romantic roles.
 E1415044 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: Berta | Statement: [The Red Mill, hasCharacter, Berta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berta
Context triple: [The Red Mill, hasCharacter, Berta]
  • A. Berta
    Berta is the sharp-tongued, no-nonsense housekeeper known for her sarcastic humor on the sitcom "Two and a Half Men."
  • B. Berta
    Berta is a fictional character in Paulo Coelho’s novel "The Devil and Miss Prym," serving as one of the villagers whose life and choices reflect the book’s central moral and spiritual dilemmas.
  • C. Berta
    Berta was a medieval queen consort of León and Castile as the wife of King Alfonso VI.
  • D. Berta
    Berta is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
  • E. Frieda
    Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
  • 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: Berta
Triple: [The Red Mill, hasCharacter, Berta]
Generated description
Berta is a fictional character from the operetta "The Red Mill," likely serving as one of its supporting comedic or romantic roles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Berta
Target entity description: Berta is a fictional character from the operetta "The Red Mill," likely serving as one of its supporting comedic or romantic roles.
  • A. Berta
    Berta is a fictional character in Paulo Coelho’s novel "The Devil and Miss Prym," serving as one of the villagers whose life and choices reflect the book’s central moral and spiritual dilemmas.
  • B. Berta
    Berta is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
  • C. Berta
    Berta is the sharp-tongued, no-nonsense housekeeper known for her sarcastic humor on the sitcom "Two and a Half Men."
  • D. Berta
    Berta was a medieval queen consort of León and Castile as the wife of King Alfonso VI.
  • E. Frieda
    Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667e505888190a05e26a3c5a0ede1 completed April 20, 2026, 5:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08347b41d8819086bd36e5e04c69ad completed May 16, 2026, 9:10 a.m.
NEDg Description generation batch_6a08359866c481908aa30ac61e18bcb0 completed May 16, 2026, 9:15 a.m.
NED2 Entity disambiguation (via description) batch_6a08361f64a08190af3305685a50f001 completed May 16, 2026, 9:17 a.m.
Created at: April 11, 2026, 11:34 p.m.