Triple

T4058082
Position Surface form Disambiguated ID Type / Status
Subject Liptov E84742 entity
Predicate hasRiver P165 FINISHED
Object Belá
Belá is a mountain river in northern Slovakia known for its clear waters, dynamic flow, and popularity among whitewater enthusiasts.
 E412488 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: Belá | Statement: [Liptov, hasRiver, Belá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Belá
Context triple: [Liptov, hasRiver, Belá]
  • A. Gödöllő
    Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
  • B. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • C. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • D. Budavár
    Budavár is the historic Buda Castle quarter of Budapest, known for its medieval streets, royal palace complex, and panoramic views over the Danube.
  • E. Komló
    Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
  • 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: Belá
Triple: [Liptov, hasRiver, Belá]
Generated description
Belá is a mountain river in northern Slovakia known for its clear waters, dynamic flow, and popularity among whitewater enthusiasts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Belá
Target entity description: Belá is a mountain river in northern Slovakia known for its clear waters, dynamic flow, and popularity among whitewater enthusiasts.
  • A. Gödöllő
    Gödöllő is a Hungarian town near Budapest best known for its historic Royal Palace, one of the largest Baroque palaces in Hungary.
  • B. Dunaújváros
    Dunaújváros is an industrial city in central Hungary known for its steel production and post-war socialist urban planning.
  • C. Kaposvár
    Kaposvár is a city in southwestern Hungary that serves as the administrative and cultural center of Somogy County.
  • D. Budavár
    Budavár is the historic Buda Castle quarter of Budapest, known for its medieval streets, royal palace complex, and panoramic views over the Danube.
  • E. Komló
    Komló is a town in southern Hungary known historically for its coal mining and hop-growing industries.
  • 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbaefcb081908aab3963dcd61a20 completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b52e31c819099f9d354c197cf00 completed March 14, 2026, 2:06 p.m.
NEDg Description generation batch_69b56c3a4b708190a55027fd3b2b76e0 completed March 14, 2026, 2:10 p.m.
NED2 Entity disambiguation (via description) batch_69b56cc2ae948190a5e13992626dd547 completed March 14, 2026, 2:12 p.m.
Created at: March 9, 2026, 3:38 p.m.