Triple

T20010962
Position Surface form Disambiguated ID Type / Status
Subject The Gashlycrumb Tinies E494586 entity
Predicate hasLetterCharacter P17387 FINISHED
Object Una 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: Una | Statement: [The Gashlycrumb Tinies, hasLetterCharacter, Una]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Una
Context triple: [The Gashlycrumb Tinies, hasLetterCharacter, Una]
  • A. Una chosen
    Una is a feminine given name of Latin origin meaning "one" or "unity," used in various cultures and literary works.
  • B. Una
    Una is a river in the Western Balkans, known for its clear turquoise waters and scenic canyons along the border of Bosnia and Herzegovina and Croatia.
  • C. Una
    Una is a town in the Gir Somnath district of Gujarat, India, known as a local commercial and transportation hub near the Saurashtra coast.
  • D. Una
    Una is a small census-designated community located in Spartanburg County, South Carolina.
  • E. Una
    Una is the live lioness who serves as the official mascot for the University of North Alabama’s athletic teams.
  • 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e662362df48190abf16129eea39985 completed April 20, 2026, 5:28 p.m.
Created at: April 11, 2026, 3:33 p.m.