Triple

T15941254
Position Surface form Disambiguated ID Type / Status
Subject Otava E386566 entity
Predicate formedByConfluenceOf P402 FINISHED
Object Křemelná
Křemelná is a river in the Czech Republic that serves as one of the main headwaters of the Otava River.
 E1184642 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: Křemelná | Statement: [Otava, formedByConfluenceOf, Křemelná]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Křemelná
Context triple: [Otava, formedByConfluenceOf, Křemelná]
  • A. Kreminna
    Kreminna is a small city in eastern Ukraine that has gained strategic significance due to its location in the Luhansk region near key transport routes and conflict zones.
  • B. Kremlyov
    Kremlyov is the historical name of the Russian town now known as Sarov, a once-closed city notable for its role in the Soviet nuclear program and its association with the monastery of St. Seraphim.
  • C. Krasny Kut
    Krasny Kut is a small town in southwestern Russia known as an administrative and agricultural center within the Saratov region.
  • D. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • E. Kremmen
    Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
  • 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: Křemelná
Triple: [Otava, formedByConfluenceOf, Křemelná]
Generated description
Křemelná is a river in the Czech Republic that serves as one of the main headwaters of the Otava River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Křemelná
Target entity description: Křemelná is a river in the Czech Republic that serves as one of the main headwaters of the Otava River.
  • A. Kreminna
    Kreminna is a small city in eastern Ukraine that has gained strategic significance due to its location in the Luhansk region near key transport routes and conflict zones.
  • B. Kremlyov
    Kremlyov is the historical name of the Russian town now known as Sarov, a once-closed city notable for its role in the Soviet nuclear program and its association with the monastery of St. Seraphim.
  • C. Krasny Kut
    Krasny Kut is a small town in southwestern Russia known as an administrative and agricultural center within the Saratov region.
  • D. Oreshek
    Oreshek is the historic Russian fortress on Lake Ladoga that later gave rise to the town of Shlisselburg.
  • E. Kremmen
    Kremmen is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156cd3a188190a1a7dcbfdd38284c completed April 16, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5bbc07c819098fd768e2e6b5b3e completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb706eb348190baba254656fc0e71 completed May 9, 2026, 10:36 p.m.
NED2 Entity disambiguation (via description) batch_69ffb7812bf08190918c1410565633e2 completed May 9, 2026, 10:38 p.m.
Created at: April 10, 2026, 4:53 a.m.