Triple

T808573
Position Surface form Disambiguated ID Type / Status
Subject Bratislava E17491 entity
Predicate locatedOnRiver P165 FINISHED
Object Morava
Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
 E101581 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: Morava | Statement: [Bratislava, locatedOnRiver, Morava]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Morava
Context triple: [Bratislava, locatedOnRiver, Morava]
  • A. Velika Morava
    Velika Morava is a major river in central Serbia formed by the confluence of the West and South Morava, flowing northward before joining the Danube.
  • B. Fiumana
    Fiumana is a small locality in the municipality of Predappio in the Emilia-Romagna region of northern Italy.
  • C. Gera
    Gera is a city in the German state of Thuringia, known for its industrial heritage and historic architecture along the White Elster river.
  • D. Orava
    Orava is a historical region in northern Slovakia and southern Poland, known for its mountainous landscapes, traditional villages, and the prominent Orava Castle.
  • E. Savo
    Savo is a town in Kenya’s Central Province known as one of the region’s notable settlements.
  • 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: Morava
Triple: [Bratislava, locatedOnRiver, Morava]
Generated description
Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Morava
Target entity description: Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
  • A. Velika Morava
    Velika Morava is a major river in central Serbia formed by the confluence of the West and South Morava, flowing northward before joining the Danube.
  • B. Fiumana
    Fiumana is a small locality in the municipality of Predappio in the Emilia-Romagna region of northern Italy.
  • C. Gera
    Gera is a city in the German state of Thuringia, known for its industrial heritage and historic architecture along the White Elster river.
  • D. Orava
    Orava is a historical region in northern Slovakia and southern Poland, known for its mountainous landscapes, traditional villages, and the prominent Orava Castle.
  • E. Savo
    Savo is a town in Kenya’s Central Province known as one of the region’s notable settlements.
  • 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_69a4937ae8a08190b5084a03d532b30e completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab256cbc8190bf75b5d5e35ff0aa completed March 1, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7a3b1a81481908c831d1f43b9d014 completed March 4, 2026, 3:14 a.m.
NEDg Description generation batch_69a7a5929de48190b01f45fbf19c72dc completed March 4, 2026, 3:22 a.m.
NED2 Entity disambiguation (via description) batch_69a7a63205308190b55b76116c0d5e7c completed March 4, 2026, 3:25 a.m.
Created at: March 1, 2026, 7:38 p.m.