Triple

T2663709
Position Surface form Disambiguated ID Type / Status
Subject Plzeň Region E54782 entity
Predicate hasMunicipalityWithExtendedPowers P41272 FINISHED
Object Manětín
Manětín is a small historic town in the western Czech Republic, noted for its Baroque chateau and well-preserved architectural heritage.
 E286684 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: Manětín | Statement: [Plzeň Region, hasMunicipalityWithExtendedPowers, Manětín]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Manětín
Context triple: [Plzeň Region, hasMunicipalityWithExtendedPowers, Manětín]
  • 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. 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.
  • C. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Náchod
    Náchod is a historic town in northeastern Bohemia, Czech Republic, known for its castle overlooking the Metuje River and its proximity to the Polish border.
  • E. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • 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: Manětín
Triple: [Plzeň Region, hasMunicipalityWithExtendedPowers, Manětín]
Generated description
Manětín is a small historic town in the western Czech Republic, noted for its Baroque chateau and well-preserved architectural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Manětín
Target entity description: Manětín is a small historic town in the western Czech Republic, noted for its Baroque chateau and well-preserved architectural heritage.
  • 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. 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.
  • C. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • D. Náchod
    Náchod is a historic town in northeastern Bohemia, Czech Republic, known for its castle overlooking the Metuje River and its proximity to the Polish border.
  • E. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • 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_69ab49e028948190b97e01d73548b1d9 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abdd1e80dc819083e04e1427d187d0 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98dc36d8819086fc739c324f0761 completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af9a14cda48190bd903495ce48a4f0 completed March 10, 2026, 4:12 a.m.
NED2 Entity disambiguation (via description) batch_69af9a7b27608190ba76048c4c8a4bae completed March 10, 2026, 4:13 a.m.
Created at: March 6, 2026, 9:54 p.m.