Triple

T3817695
Position Surface form Disambiguated ID Type / Status
Subject Prague Metro E84295 entity
Predicate hasStation P35 FINISHED
Object 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.
 E393165 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: Zličín | Statement: [Prague Metro, hasStation, Zličín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Zličín
Context triple: [Prague Metro, hasStation, Zličín]
  • A. Mělník
    Mělník is a historic Czech town north of Prague, known for its wine production and its location at the confluence of the Elbe and Vltava rivers.
  • B. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • C. 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.
  • D. 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.
  • 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: Zličín
Triple: [Prague Metro, hasStation, Zličín]
Generated description
Zličín is a district in the western part of Prague that serves as a key transport hub and terminus of a Prague Metro line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Zličín
Target entity description: Zličín is a district in the western part of Prague that serves as a key transport hub and terminus of a Prague Metro line.
  • A. Mělník
    Mělník is a historic Czech town north of Prague, known for its wine production and its location at the confluence of the Elbe and Vltava rivers.
  • B. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • C. 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.
  • D. 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.
  • 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_69aed931f5908190be2c07af66d4df25 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeea5e41ec81908ed7e1ccc2713622 completed March 9, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503f549b0819088b64ddb3f38238f completed March 14, 2026, 6:45 a.m.
NEDg Description generation batch_69b504e663a08190b2d462da2b725469 completed March 14, 2026, 6:49 a.m.
NED2 Entity disambiguation (via description) batch_69b50534242c8190a1d4658e7896c2be completed March 14, 2026, 6:50 a.m.
Created at: March 9, 2026, 3:17 p.m.