Triple

T17742756
Position Surface form Disambiguated ID Type / Status
Subject Serbian Podrinje E442904 entity
Predicate containsTown P847 FINISHED
Object Ljubovija NE NERFINISHED

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: Ljubovija | Statement: [Serbian Podrinje, containsTown, Ljubovija]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ljubovija
Context triple: [Serbian Podrinje, containsTown, Ljubovija]
  • A. Ljubovija chosen
    Ljubovija is a small Serbian town on the Drina River known for its scenic mountainous surroundings and role as a local administrative and cultural center.
  • B. Lubja
    Lubja is a small village located within Viimsi Parish in northern Estonia, near the capital city of Tallinn.
  • C. Ľubietová
    Ľubietová is a historic village in central Slovakia known for its former copper and iron ore mining activities and role in the country’s mining heritage.
  • D. Ľubiša
    Ľubiša is a village in northeastern Slovakia, known as the birthplace of the country’s first president, Michal Kováč.
  • E. Dajla
    Dajla is an alternative name for Dakhla, a coastal city in Western Sahara known for its fishing industry and popular kitesurfing spots.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e47ace58988190b927ca29af7a8b77 completed April 19, 2026, 6:48 a.m.
Created at: April 10, 2026, 10:09 a.m.