Triple

T12354326
Position Surface form Disambiguated ID Type / Status
Subject Kyustendil Province E294568 entity
Predicate hasTown P847 FINISHED
Object Sapareva Banya
Sapareva Banya is a Bulgarian spa town renowned for its hot mineral springs and the hottest geyser in continental Europe.
E988607 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: Sapareva Banya | Statement: [Kyustendil Province, hasTown, Sapareva Banya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sapareva Banya
Context triple: [Kyustendil Province, hasTown, Sapareva Banya]
  • A. Bansko
    Bansko is a Bulgarian mountain town renowned as one of Eastern Europe’s leading ski and winter sports resorts.
  • B. Sliven
    Sliven is a city in eastern Bulgaria known for its textile industry, historic role in Bulgarian national revival, and location near the eastern Balkan Mountains.
  • C. Svishtov
    Svishtov is a town in northern Bulgaria on the Danube River, known for its historical significance, including proximity to the ancient Roman military site of Novae.
  • D. Butovo
    Butovo is a residential district in the southern part of Moscow, Russia, known for its large housing estates and rapid post-Soviet urban development.
  • E. Kazanlak
    Kazanlak is a town in central Bulgaria known for its rich Thracian heritage and rose oil production in the Valley of the Roses.
  • 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: Sapareva Banya
Triple: [Kyustendil Province, hasTown, Sapareva Banya]
Generated description
Sapareva Banya is a Bulgarian spa town renowned for its hot mineral springs and the hottest geyser in continental Europe.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sapareva Banya
Target entity description: Sapareva Banya is a Bulgarian spa town renowned for its hot mineral springs and the hottest geyser in continental Europe.
  • A. Bansko
    Bansko is a Bulgarian mountain town renowned as one of Eastern Europe’s leading ski and winter sports resorts.
  • B. Sliven
    Sliven is a city in eastern Bulgaria known for its textile industry, historic role in Bulgarian national revival, and location near the eastern Balkan Mountains.
  • C. Svishtov
    Svishtov is a town in northern Bulgaria on the Danube River, known for its historical significance, including proximity to the ancient Roman military site of Novae.
  • D. Butovo
    Butovo is a residential district in the southern part of Moscow, Russia, known for its large housing estates and rapid post-Soviet urban development.
  • E. Kazanlak
    Kazanlak is a town in central Bulgaria known for its rich Thracian heritage and rose oil production in the Valley of the Roses.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f8bc60c8190b0ceb84093e70db4 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f655608a0c81908002f9d79d017ded completed May 2, 2026, 7:49 p.m.
NEDg Description generation batch_69f6566dccc0819085e059c7b0288f6c completed May 2, 2026, 7:54 p.m.
NED2 Entity disambiguation (via description) batch_69f657aec8fc8190b3b08ccb95595958 completed May 2, 2026, 7:59 p.m.
Created at: April 8, 2026, 9:54 p.m.