Triple

T11923218
Position Surface form Disambiguated ID Type / Status
Subject Zora Vesecká E283710 entity
Predicate nameInLatinAlphabet P22444 FINISHED
Object Zora Vesecká E283710 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: Zora Vesecká | Statement: [Zora Vesecká, nameInLatinAlphabet, Zora Vesecká]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zora Vesecká
Context triple: [Zora Vesecká, nameInLatinAlphabet, Zora Vesecká]
  • A. Zora Vesecká chosen
    Zora Vesecká is a Czech individual whose given name is Zora, a common female name in Slavic countries.
  • B. Zora Jandová
    Zora Jandová is a Czech actress, singer, and former radio journalist known for her work in film, television, and music.
  • C. Zora Rozsypalová
    Zora Rozsypalová was a Czech actress known for her work in theater and film during the mid-20th century.
  • D. Selma Ježková
    Selma Ježková is the tragic, near-blind Czech immigrant and factory worker portrayed by Björk in Lars von Trier’s musical drama film "Dancer in the Dark."
  • E. Anna Geislerová
    Anna Geislerová is a prominent Czech film and television actress known for her acclaimed performances in both domestic and international productions.
  • 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_69d6ab2ce9c48190b5d39511b524f666 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e8e2fc648190a446c1917db1c7d9 completed April 10, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69f44042cf1c81909de44acfe1202482 completed May 1, 2026, 5:55 a.m.
Created at: April 8, 2026, 9:45 p.m.