Triple

T12662088
Position Surface form Disambiguated ID Type / Status
Subject Arnstadt E302448 entity
Predicate hasTwinTown P919 FINISHED
Object Dubí
Dubí is a small spa town in the Ústí nad Labem Region of the Czech Republic, known for its porcelain production and location in the Ore Mountains near the German border.
 E1089910 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: Dubí | Statement: [Arnstadt, hasTwinTown, Dubí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dubí
Context triple: [Arnstadt, hasTwinTown, Dubí]
  • A. 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.
  • B. Vyhne
    Vyhne is a historic village in central Slovakia known for its former mining activities, spa traditions, and scenic mountainous surroundings.
  • C. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • D. Chrudim
    Chrudim is a historic town in the Pardubice Region of the Czech Republic, known for its well-preserved medieval center and cultural heritage.
  • E. 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.
  • 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: Dubí
Triple: [Arnstadt, hasTwinTown, Dubí]
Generated description
Dubí is a small spa town in the Ústí nad Labem Region of the Czech Republic, known for its porcelain production and location in the Ore Mountains near the German border.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dubí
Target entity description: Dubí is a small spa town in the Ústí nad Labem Region of the Czech Republic, known for its porcelain production and location in the Ore Mountains near the German border.
  • A. 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.
  • B. Vyhne
    Vyhne is a historic village in central Slovakia known for its former mining activities, spa traditions, and scenic mountainous surroundings.
  • C. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • D. Chrudim
    Chrudim is a historic town in the Pardubice Region of the Czech Republic, known for its well-preserved medieval center and cultural heritage.
  • E. 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.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617c5b888190b37d4ede139bb49e completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd32359c54819098349d7d1c1e454f completed May 8, 2026, 12:45 a.m.
NEDg Description generation batch_69fd335a496881908689b5769bb677ae completed May 8, 2026, 12:50 a.m.
NED2 Entity disambiguation (via description) batch_69fd3445422c8190a22eaa4bef5fdf76 completed May 8, 2026, 12:54 a.m.
Created at: April 9, 2026, 5:19 p.m.