Triple

T4071414
Position Surface form Disambiguated ID Type / Status
Subject Václav Havel Airport Prague E86655 entity
Predicate locatedIn P40 FINISHED
Object 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.
 E422250 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: Ruzyně | Statement: [Václav Havel Airport Prague, locatedIn, Ruzyně]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ruzyně
Context triple: [Václav Havel Airport Prague, locatedIn, Ruzyně]
  • A. Říčany
    Říčany is a town in the Czech Republic, located just southeast of Prague and known as a popular residential and commuter suburb with historical roots.
  • B. Svitavy
    Svitavy is a town in the Czech Republic best known as the birthplace of Oskar Schindler, the industrialist who saved hundreds of Jews during the Holocaust.
  • C. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Zličín
    Zličín is a district in the western part of Prague that serves as a key transport hub and terminus of a Prague Metro line.
  • E. Broumov
    Broumov is a historic town in northeastern Bohemia, Czech Republic, known for its Benedictine monastery and proximity to the Broumov Walls sandstone rock formations.
  • 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: Ruzyně
Triple: [Václav Havel Airport Prague, locatedIn, Ruzyně]
Generated description
Ruzyně is a district in the western part of Prague, Czech Republic, best known as the location of the city’s main international airport.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ruzyně
Target entity description: Ruzyně is a district in the western part of Prague, Czech Republic, best known as the location of the city’s main international airport.
  • A. Říčany
    Říčany is a town in the Czech Republic, located just southeast of Prague and known as a popular residential and commuter suburb with historical roots.
  • B. Svitavy
    Svitavy is a town in the Czech Republic best known as the birthplace of Oskar Schindler, the industrialist who saved hundreds of Jews during the Holocaust.
  • C. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Zličín
    Zličín is a district in the western part of Prague that serves as a key transport hub and terminus of a Prague Metro line.
  • E. Broumov
    Broumov is a historic town in northeastern Bohemia, Czech Republic, known for its Benedictine monastery and proximity to the Broumov Walls sandstone rock formations.
  • 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_69aed93ebe448190a1f1686e28740ac9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefc20ed788190bd935082a348a05d completed March 9, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69b595ffd8b4819099bb5698d9cc10e0 completed March 14, 2026, 5:08 p.m.
NEDg Description generation batch_69b59695c99481909a061751eaccbb25 completed March 14, 2026, 5:10 p.m.
NED2 Entity disambiguation (via description) batch_69b59a568e288190a87ba03b181f27df completed March 14, 2026, 5:26 p.m.
Created at: March 9, 2026, 3:38 p.m.