Triple

T6627816
Position Surface form Disambiguated ID Type / Status
Subject Two and a Half Men E149847 entity
Predicate recurringCharacter P12208 FINISHED
Object Berta
Berta is the sharp-tongued, no-nonsense housekeeper known for her sarcastic humor on the sitcom "Two and a Half Men."
 E600888 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: [Two and a Half Men, recurringCharacter, Berta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Berta
Context triple: [Two and a Half Men, recurringCharacter, Berta]
  • 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. Frieda
    Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
  • D. Huberta
    Huberta is a feminine given name of Dutch origin, used in full or as part of compound names such as Everdine Huberta van Wijnbergen.
  • E. Baerbel
    Baerbel is a feminine given name of German origin, commonly used as an alternative spelling of Bärbel.
  • 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: [Two and a Half Men, recurringCharacter, Berta]
Generated description
Berta is the sharp-tongued, no-nonsense housekeeper known for her sarcastic humor on the sitcom "Two and a Half Men."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Berta
Target entity description: Berta is the sharp-tongued, no-nonsense housekeeper known for her sarcastic humor on the sitcom "Two and a Half Men."
  • 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. Frieda
    Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
  • D. Huberta
    Huberta is a feminine given name of Dutch origin, used in full or as part of compound names such as Everdine Huberta van Wijnbergen.
  • E. Baerbel
    Baerbel is a feminine given name of German origin, commonly used as an alternative spelling of Bärbel.
  • 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afa2e4a48190ba3c70013bab14f2 completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbe690548190a771bb1ec8d3aacf completed March 27, 2026, 6:26 p.m.
NEDg Description generation batch_69c6cd0a98908190a5725c49bad7589d completed March 27, 2026, 6:31 p.m.
NED2 Entity disambiguation (via description) batch_69c6cdcf14508190876faa73f5eec884 completed March 27, 2026, 6:34 p.m.
Created at: March 27, 2026, 1:59 p.m.