Triple

T23544482
Position Surface form Disambiguated ID Type / Status
Subject Dolly Sinatra E577851 entity
Predicate givenName P17 FINISHED
Object Natalina NE NERFINISHED

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: Natalina | Statement: [Dolly Sinatra, givenName, Natalina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Natalina
Context triple: [Dolly Sinatra, givenName, Natalina]
  • A. Natalina chosen
    Natalina is an Italian feminine given name, often used in regions with strong Italian cultural and linguistic roots.
  • B. Marinka
    Marinka is a 1945 operetta by Hungarian composer Emmerich Kálmán, based on the story of the assassination of Archduke Franz Ferdinand in Sarajevo.
  • C. Aroona
    Aroona is a coastal suburb on Queensland’s Sunshine Coast in Australia, known for its residential character and proximity to beaches and local amenities.
  • D. Tona
    Tona is a municipality in the comarca of Osona in Catalonia, Spain, known for its rural character and proximity to the city of Vic.
  • E. Jacinta
    Jacinta is a feminine given name of Spanish and Portuguese origin, famously borne by Jacinta Marto, one of the child visionaries of Fátima.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245f9d5d08190a4a20004e1784e20 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ae1ef55c8190a93c33e704ec3b5a completed April 29, 2026, 7:07 a.m.
Created at: April 17, 2026, 6:11 p.m.