Triple

T1451068
Position Surface form Disambiguated ID Type / Status
Subject Olga Taussky-Todd E31291 entity
Predicate placeOfBirth P1 FINISHED
Object Olomouc E191130 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: Olomouc | Statement: [Olga Taussky-Todd, placeOfBirth, Olomouc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Olomouc
Context triple: [Olga Taussky-Todd, placeOfBirth, Olomouc]
  • A. Olomouc chosen
    Olomouc is a historic city in the eastern Czech Republic known for its well-preserved old town, Baroque architecture, and UNESCO-listed Holy Trinity Column.
  • B. Opava
    Opava is a historic city in the Czech Republic’s Silesian region, known as a former political and cultural center of Silesia.
  • C. Hradec Králové
    Hradec Králové is a historic city in the Czech Republic known for its educational institutions, modernist architecture, and role as a regional cultural and economic center.
  • D. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • E. Ústí nad Labem
    Ústí nad Labem is an industrial city in the north of the Czech Republic, known as a major transport hub and river port in the Bohemian region.
  • 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_69a499171a28819085b993a3ac78e363 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c57bc0908190a57e6bc3d20d5e3c completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69adc986352881909dcc435095bc0f8f completed March 8, 2026, 7:09 p.m.
Created at: March 1, 2026, 8 p.m.