Triple

T9085118
Position Surface form Disambiguated ID Type / Status
Subject Beroun E217732 entity
Predicate locatedOnRiver P165 FINISHED
Object Litavka
Litavka is a river in the Czech Republic that flows through the town of Beroun before joining the Berounka River.
 E777332 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: Litavka | Statement: [Beroun, locatedOnRiver, Litavka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Litavka
Context triple: [Beroun, locatedOnRiver, Litavka]
  • A. Chrudimka
    Chrudimka is a river in the Czech Republic that flows through the Pardubice Region and is a tributary of the Elbe.
  • B. Lipnik
    Lipnik is a village and administrative district in south-central Poland, located within the Świętokrzyskie Voivodeship.
  • C. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • D. Pálava
    Pálava is a renowned wine-producing region in the Czech Republic, noted for its limestone hills and high-quality white wines, especially aromatic varieties.
  • E. Kriváň
    Kriváň is a prominent and symbolically important peak in Slovakia’s High Tatras, often regarded as a national symbol and popular hiking destination.
  • 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: Litavka
Triple: [Beroun, locatedOnRiver, Litavka]
Generated description
Litavka is a river in the Czech Republic that flows through the town of Beroun before joining the Berounka River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Litavka
Target entity description: Litavka is a river in the Czech Republic that flows through the town of Beroun before joining the Berounka River.
  • A. Chrudimka
    Chrudimka is a river in the Czech Republic that flows through the Pardubice Region and is a tributary of the Elbe.
  • B. Lipnik
    Lipnik is a village and administrative district in south-central Poland, located within the Świętokrzyskie Voivodeship.
  • C. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • D. Pálava
    Pálava is a renowned wine-producing region in the Czech Republic, noted for its limestone hills and high-quality white wines, especially aromatic varieties.
  • E. Kriváň
    Kriváň is a prominent and symbolically important peak in Slovakia’s High Tatras, often regarded as a national symbol and popular hiking destination.
  • 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_69ca83d7a0388190ba1af89ed7ba36f9 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc960d0b008190b0e9e61fac45101d completed April 1, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69d017c893fc819087d18db2383b9bb4 completed April 3, 2026, 7:40 p.m.
NEDg Description generation batch_69d01908d7b08190ab159048f25924d5 completed April 3, 2026, 7:46 p.m.
NED2 Entity disambiguation (via description) batch_69d019b9be10819091e25d5b3a8d26c1 completed April 3, 2026, 7:49 p.m.
Created at: March 30, 2026, 7:13 p.m.