Triple

T4297073
Position Surface form Disambiguated ID Type / Status
Subject Brno region E99740 entity
Predicate containsTown P847 FINISHED
Object Rousínov
Rousínov is a small town in the South Moravian Region of the Czech Republic, known for its traditional furniture-making industry and proximity to the city of Brno.
E433624 NE FINISHED

How this triple was built (4 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: Rousínov | Statement: [Brno region, containsTown, Rousínov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rousínov
Context triple: [Brno region, containsTown, Rousínov]
  • A. Ruzinov
    Ružinov is a borough of Bratislava, Slovakia, known as a major residential and commercial district of the capital.
  • B. Ruzyně
    Ruzyně is a district in the western part of Prague, Czech Republic, best known as the location of the city’s main international airport.
  • C. Sokolov
    Sokolov is a town in the Karlovy Vary Region of the Czech Republic, known for its historical center and location in the Ohře River valley.
  • D. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • E. Nymburk
    Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe River.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Rousínov
Triple: [Brno region, containsTown, Rousínov]
Generated description
Rousínov is a small town in the South Moravian Region of the Czech Republic, known for its traditional furniture-making industry and proximity to the city of Brno.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rousínov
Target entity description: Rousínov is a small town in the South Moravian Region of the Czech Republic, known for its traditional furniture-making industry and proximity to the city of Brno.
  • A. Ruzinov
    Ružinov is a borough of Bratislava, Slovakia, known as a major residential and commercial district of the capital.
  • B. Ruzyně
    Ruzyně is a district in the western part of Prague, Czech Republic, best known as the location of the city’s main international airport.
  • C. Sokolov
    Sokolov is a town in the Karlovy Vary Region of the Czech Republic, known for its historical center and location in the Ohře River valley.
  • D. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • E. Nymburk
    Nymburk is a historic town in the Czech Republic known for its medieval fortifications and location on the Elbe River.
  • F. None of above. chosen

Provenance (5 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_69b3455175088190aa79c6e03b86647e completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509aebd48190af38f2e37f07869a completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5db8a3a0481909d24f214f56bd21e completed March 14, 2026, 10:04 p.m.
NEDg Description generation batch_69b5df52a494819086c89a1818fabe5b completed March 14, 2026, 10:21 p.m.
NED2 Entity disambiguation (via description) batch_69b5dfb71ba48190b412016d11a9efa5 completed March 14, 2026, 10:22 p.m.
Created at: March 12, 2026, 11:08 p.m.