Triple

T23068053
Position Surface form Disambiguated ID Type / Status
Subject Tereza Vávrová E575106 entity
Predicate hasNameComponent P24447 FINISHED
Object Tereza 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: Tereza | Statement: [Tereza Vávrová, hasNameComponent, Tereza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tereza
Context triple: [Tereza Vávrová, hasNameComponent, Tereza]
  • A. Tereza chosen
    Tereza is a feminine given name, commonly used in various European countries as a variant of Theresa.
  • B. Tereza Vávrová
    Tereza Vávrová is a notable bearer of the Czech surname Vávrová, recognized enough to be specifically cited in reference to the name.
  • C. Antónia
    Antónia is a feminine given name commonly used in various European languages, often as a variant of Antonia.
  • D. Veronika Bellmann
    Veronika Bellmann is a German politician known for her long-standing membership in the Bundestag representing the Christian Democratic Union (CDU).
  • E. Milada
    Milada is a feminine given name of Slavic origin, particularly common in Czech and Slovak cultures.
  • 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_69e245bd6e4c8190bb8942245b68cad5 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f189a5aa4081909b3f0dc92877323d completed April 29, 2026, 4:31 a.m.
Created at: April 17, 2026, 3:55 p.m.