Triple

T5033313
Position Surface form Disambiguated ID Type / Status
Subject Margareta E113357 entity
Predicate hasDiminutive P456 FINISHED
Object Greta E114897 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: Greta | Statement: [Margareta, hasDiminutive, Greta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greta
Context triple: [Margareta, hasDiminutive, Greta]
  • A. Greta
    Greta is a small town located within the Hunter Region of New South Wales, Australia.
  • B. Greta chosen
    Greta is a feminine given name, commonly used as a diminutive or variant of names like Margaret in various European languages.
  • C. Katrin
    Katrin is a feminine given name, commonly used in various European countries, that is a variant of the name Catherine.
  • D. Greta Lovisa Gustafsson
    Greta Lovisa Gustafsson, better known as Greta Garbo, was a legendary Swedish-American film actress renowned for her enigmatic screen presence and iconic roles during Hollywood’s silent and early sound eras.
  • E. Katarina Frostenson
    Katarina Frostenson is a Swedish poet, writer, and former member of the Swedish Academy known for her influential and experimental contributions to contemporary Swedish literature.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73b68d8c8190b8e04fb406abdb0f completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea477efec8190a84a0186f5517a43 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:36 p.m.