Triple

T18413345
Position Surface form Disambiguated ID Type / Status
Subject The Last Letter Home E441819 entity
Predicate hasLiteraryCharacter P12208 FINISHED
Object Kristina 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: Kristina | Statement: [The Last Letter Home, hasLiteraryCharacter, Kristina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristina
Context triple: [The Last Letter Home, hasLiteraryCharacter, Kristina]
  • A. Kristina chosen
    Kristina is a feminine given name commonly used in various European countries, often considered a variant of Christina.
  • B. Katarina Stenbock
    Katarina Stenbock was a Swedish noblewoman who became the third and last wife of King Gustav I of Sweden and served as Queen consort in the 16th century.
  • C. Ulrike
    Ulrike is a German given name, typically feminine, derived from the name Ulrich and associated with German-speaking countries.
  • D. Kerstin
    Kerstin is a feminine given name of Scandinavian origin, particularly common in Sweden and other Nordic countries.
  • E. Kristina Lugn
    Kristina Lugn was a Swedish poet, playwright, and member of the Swedish Academy known for her darkly humorous and psychologically incisive works.
  • 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_69d8b9eb8a508190a942fd75ebd8b1dc completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e51a259c1c819094e710bb4a7ace75 completed April 19, 2026, 6:08 p.m.
Created at: April 10, 2026, 10:47 a.m.