Triple

T11021301
Position Surface form Disambiguated ID Type / Status
Subject Harrachov E260494 entity
Predicate hasPart P35 FINISHED
Object Rýžoviště
Rýžoviště is a locality within the Czech mountain town of Harrachov, known as a base for tourism and access to nearby natural and ski areas in the Krkonoše Mountains.
E900316 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: Rýžoviště | Statement: [Harrachov, hasPart, Rýžoviště]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rýžoviště
Context triple: [Harrachov, hasPart, Rýžoviště]
  • A. 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.
  • B. Pohořelice
    Pohořelice is a small town in the South Moravian Region of the Czech Republic, known for its agricultural surroundings and proximity to the city of Brno.
  • C. Kaliště
    Kaliště is a small village in the Czech Republic best known as the birthplace of composer Gustav Mahler.
  • D. Chrudimka
    Chrudimka is a river in the Czech Republic that flows through the Pardubice Region and is a tributary of the Elbe.
  • E. Smiřice
    Smiřice is a small town in the Hradec Králové Region of the Czech Republic, known for its historic chateau and Baroque church.
  • 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: Rýžoviště
Triple: [Harrachov, hasPart, Rýžoviště]
Generated description
Rýžoviště is a locality within the Czech mountain town of Harrachov, known as a base for tourism and access to nearby natural and ski areas in the Krkonoše Mountains.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rýžoviště
Target entity description: Rýžoviště is a locality within the Czech mountain town of Harrachov, known as a base for tourism and access to nearby natural and ski areas in the Krkonoše Mountains.
  • A. 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.
  • B. Pohořelice
    Pohořelice is a small town in the South Moravian Region of the Czech Republic, known for its agricultural surroundings and proximity to the city of Brno.
  • C. Kaliště
    Kaliště is a small village in the Czech Republic best known as the birthplace of composer Gustav Mahler.
  • D. Chrudimka
    Chrudimka is a river in the Czech Republic that flows through the Pardubice Region and is a tributary of the Elbe.
  • E. Smiřice
    Smiřice is a small town in the Hradec Králové Region of the Czech Republic, known for its historic chateau and Baroque church.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797bb6eec81909d8004af31f307f7 completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e374f64b3c8190b0b55193f81d3bc5 completed April 18, 2026, 12:11 p.m.
NEDg Description generation batch_69e37ab860f48190808ba0076cfa9c98 completed April 18, 2026, 12:36 p.m.
NED2 Entity disambiguation (via description) batch_69e3864dd0d48190b3fd81381f5d7418 completed April 18, 2026, 1:25 p.m.
Created at: April 8, 2026, 9:25 p.m.