Triple

T8251688
Position Surface form Disambiguated ID Type / Status
Subject Blue Nile State E192972 entity
Predicate hasEthnicGroup P1898 FINISHED
Object Berta E255792 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 | Statement: [Blue Nile State, hasEthnicGroup, Berta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berta
Context triple: [Blue Nile State, hasEthnicGroup, 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 chosen
    Berta is a Nilo-Saharan language spoken primarily in parts of Sudan and Ethiopia.
  • D. Frieda
    Frieda is a 1947 British drama film produced by Michael Balcon that explores post-World War II tensions and prejudice in England.
  • E. 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.
  • 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_69ca82de7b8c81908d8106f8a53cff9b completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78ca4b0881909bb1fb550dba59e7 completed March 31, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd3540a0988190b8e48988279403db completed April 1, 2026, 3:09 p.m.
Created at: March 30, 2026, 5:48 p.m.