Triple

T6627820
Position Surface form Disambiguated ID Type / Status
Subject Two and a Half Men E149847 entity
Predicate portrayedBy P1507 FINISHED
Object Berta – Conchata Ferrell E174326 NE FINISHED

How this triple was built (2 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 – Conchata Ferrell | Statement: [Two and a Half Men, portrayedBy, Berta – Conchata Ferrell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berta – Conchata Ferrell
Context triple: [Two and a Half Men, portrayedBy, Berta – Conchata Ferrell]
  • A. Bette
    Bette is the given name of American singer, actress, and comedian Bette Midler.
  • B. Berta chosen
    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 is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
  • D. Betty
    Betty is a feminine given name, often a diminutive of Elizabeth, that has been widely used in English-speaking countries.
  • E. Betty
    "Betty" is the Allied reporting name for the Mitsubishi G4M, a Japanese World War II twin-engine land-based bomber known for its long range and vulnerability due to lack of armor and self-sealing fuel tanks.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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.
Created at: March 27, 2026, 1:59 p.m.