Triple

T22743864
Position Surface form Disambiguated ID Type / Status
Subject Jonas Valančiūnas E562491 entity
Predicate placeOfBirth P1 FINISHED
Object Utena 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: Utena | Statement: [Jonas Valančiūnas, placeOfBirth, Utena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Utena
Context triple: [Jonas Valančiūnas, placeOfBirth, Utena]
  • A. Utena chosen
    Utena is a town in northeastern Lithuania that serves as an important regional center in the historical region of Aukštaitija.
  • B. Suyasha
    Suyasha is a figure from Hindu tradition known primarily as the consort of Nandi, the divine bull and devoted attendant of Lord Shiva.
  • C. Ryoko
    Ryoko is a powerful, mischievous space pirate and one of the central female leads in the Tenchi Muyo! anime franchise.
  • D. Mai Shiranui
    Mai Shiranui is a popular and iconic kunoichi (female ninja) character from SNK’s fighting games, known for her revealing outfit, agile fighting style, and fiery fan-based attacks.
  • E. Sunshine Sakae
    Sunshine Sakae is a prominent entertainment and shopping complex in Nagoya, Japan, known for its distinctive Ferris wheel and variety of retail, dining, and leisure facilities.
  • 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1797590f08190a784f73fcd27b101 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:23 p.m.