Triple

T12402170
Position Surface form Disambiguated ID Type / Status
Subject Blagoevgrad Province E296283 entity
Predicate containsTown P847 FINISHED
Object Bansko E284306 NE FINISHED

How this triple was built (2 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: [Blagoevgrad Province, containsTown, Bansko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bansko
Context triple: [Blagoevgrad Province, containsTown, Bansko]
  • A. Bansko chosen
    Bansko is a Bulgarian mountain town renowned as one of Eastern Europe’s leading ski and winter sports resorts.
  • B. Sapareva Banya
    Sapareva Banya is a Bulgarian spa town renowned for its hot mineral springs and the hottest geyser in continental Europe.
  • C. Smolyan
    Smolyan is a Bulgarian town known as an administrative, cultural, and tourist center in the Rhodope Mountains.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d477004819095e65ef6f70c69d9 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671852f588190924ded1c0a360b47 completed May 2, 2026, 9:49 p.m.
Created at: April 8, 2026, 9:55 p.m.