Triple

T1335506
Position Surface form Disambiguated ID Type / Status
Subject Roberta E28738 entity
Predicate hasVariantSpelling P457 FINISHED
Object Roberta (unchanged across many languages) E28738 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: Roberta (unchanged across many languages) | Statement: [Roberta, hasVariantSpelling, Roberta (unchanged across many languages)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roberta (unchanged across many languages)
Context triple: [Roberta, hasVariantSpelling, Roberta (unchanged across many languages)]
  • A. Roberta chosen
    Roberta is a feminine given name commonly used in various languages, derived from the masculine name Robert.
  • B.
    Ró is a shortened given name or nickname derived from the name Róbert.
  • C. Roberta, Georgia
    Roberta, Georgia is a small city in Crawford County known as a rural community and local crossroads in central Georgia.
  • D. Robina
    Robina is a master-planned residential and commercial suburb on the Gold Coast in Queensland, Australia, known for its large shopping centre and modern urban design.
  • E. Johanna
    Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1ecb5208190a9eadda113c91e66 completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62b9bd081909dbe22cbea03f21f completed March 8, 2026, 12:43 a.m.
Created at: March 1, 2026, 7:55 p.m.