Triple

T10092714
Position Surface form Disambiguated ID Type / Status
Subject Sajó E215781 entity
Predicate hasNameInSlovak P25642 FINISHED
Object Slaná
Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
 E847787 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: Slaná | Statement: [Sajó, hasNameInSlovak, Slaná]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Slaná
Context triple: [Sajó, hasNameInSlovak, Slaná]
  • A. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • B. Vodňany
    Vodňany is a small historic town in the South Bohemian Region of the Czech Republic, known for its traditional fishpond farming and picturesque rural character.
  • C. Svatava
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • D. Moravice
    Moravice is a river in the northern part of the historical Moravia region of the Czech Republic.
  • E. Dôle
    Dôle is a traditional Swiss red wine blend from the Valais region, typically made from Pinot Noir and Gamay grapes and known for its fruity, approachable character.
  • 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: Slaná
Triple: [Sajó, hasNameInSlovak, Slaná]
Generated description
Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Slaná
Target entity description: Slaná is a river in central Europe that flows through Slovakia and Hungary, where it is known as the Sajó.
  • A. Slaný
    Slaný is a historic town in the Czech Republic known for its medieval center and location northwest of Prague.
  • B. Vodňany
    Vodňany is a small historic town in the South Bohemian Region of the Czech Republic, known for its traditional fishpond farming and picturesque rural character.
  • C. Svatava
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • D. Moravice
    Moravice is a river in the northern part of the historical Moravia region of the Czech Republic.
  • E. Dôle
    Dôle is a traditional Swiss red wine blend from the Valais region, typically made from Pinot Noir and Gamay grapes and known for its fruity, approachable character.
  • 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_69ca83a4947c8190823a7495dc5d96ed completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd05c3c0c8190927580717429a4e5 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3174109988190b703bb5b7c89c5c2 completed April 6, 2026, 2:15 a.m.
NEDg Description generation batch_69d31b67a62c81909ce3f5667e71516c completed April 6, 2026, 2:33 a.m.
NED2 Entity disambiguation (via description) batch_69d31f31c95881909cbf8f7154718447 completed April 6, 2026, 2:49 a.m.
Created at: March 30, 2026, 9:01 p.m.