Triple

T2638944
Position Surface form Disambiguated ID Type / Status
Subject Pirin Mountains E62816 entity
Predicate nearestTown P350 FINISHED
Object Bansko
Bansko is a Bulgarian mountain town renowned as one of Eastern Europe’s leading ski and winter sports resorts.
 E284306 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: Bansko | Statement: [Pirin Mountains, nearestTown, Bansko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bansko
Context triple: [Pirin Mountains, nearestTown, Bansko]
  • A. Blagoevgrad
    Blagoevgrad is a city in southwestern Bulgaria known as a regional cultural and educational center, home to several universities and a vibrant student population.
  • B. Borovets resort
    Borovets resort is one of Bulgaria’s oldest and most popular mountain and ski resorts, located on the northern slopes of the Rila Mountains.
  • C. Plovdiv
    Plovdiv is Bulgaria’s second-largest city and one of Europe’s oldest continuously inhabited urban centers, known for its Roman amphitheater, Old Town, and rich cultural heritage.
  • D. Silistra
    Silistra is a historic city in northeastern Bulgaria on the Danube River, known as an important cultural and economic center of the Dobruja region.
  • E. Pliska
    Pliska was the first capital city of the early medieval First Bulgarian Empire, serving as its political and administrative center.
  • 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: Bansko
Triple: [Pirin Mountains, nearestTown, Bansko]
Generated description
Bansko is a Bulgarian mountain town renowned as one of Eastern Europe’s leading ski and winter sports resorts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bansko
Target entity description: Bansko is a Bulgarian mountain town renowned as one of Eastern Europe’s leading ski and winter sports resorts.
  • A. Blagoevgrad
    Blagoevgrad is a city in southwestern Bulgaria known as a regional cultural and educational center, home to several universities and a vibrant student population.
  • B. Borovets resort
    Borovets resort is one of Bulgaria’s oldest and most popular mountain and ski resorts, located on the northern slopes of the Rila Mountains.
  • C. Plovdiv
    Plovdiv is Bulgaria’s second-largest city and one of Europe’s oldest continuously inhabited urban centers, known for its Roman amphitheater, Old Town, and rich cultural heritage.
  • D. Silistra
    Silistra is a historic city in northeastern Bulgaria on the Danube River, known as an important cultural and economic center of the Dobruja region.
  • E. Pliska
    Pliska was the first capital city of the early medieval First Bulgarian Empire, serving as its political and administrative center.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8fafad08190939b08558fea6abd completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af90b628748190bdbb23f1d85bc3fd completed March 10, 2026, 3:32 a.m.
NEDg Description generation batch_69af91c6de008190ad8fb3a3c06472cb completed March 10, 2026, 3:36 a.m.
NED2 Entity disambiguation (via description) batch_69af9253953c8190a8e18c92d66263cc completed March 10, 2026, 3:38 a.m.
Created at: March 6, 2026, 9:53 p.m.