Triple

T4537200
Position Surface form Disambiguated ID Type / Status
Subject Kotor E107434 entity
Predicate nearbyCity P350 FINISHED
Object Budva E142917 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: Budva | Statement: [Kotor, nearbyCity, Budva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Budva
Context triple: [Kotor, nearbyCity, Budva]
  • A. Budva chosen
    Budva is a historic coastal town on the Adriatic Sea, famous for its medieval old town, sandy beaches, and role as a major tourist destination in Montenegro.
  • B. Herceg Novi
    Herceg Novi is a coastal town in western Montenegro known for its historic old town, fortresses, and scenic location at the entrance to the Bay of Kotor.
  • C. Makarska
    Makarska is a coastal town and popular tourist resort on the Adriatic Sea in southern Croatia, known for its beaches and the nearby Biokovo mountain range.
  • D. Trogir
    Trogir is a historic coastal town in Croatia renowned for its well-preserved medieval architecture and UNESCO-listed old town on the Adriatic Sea.
  • E. Podgorica
    Podgorica is the capital and largest city of Montenegro, serving as its political, economic, and cultural center in the Balkans.
  • 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_69bd43f922788190b7edfa294e39b178 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57b78b8481909d79131723d4be22 completed March 20, 2026, 2:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be101759e08190b3190c6e8961b3f7 completed March 21, 2026, 3:27 a.m.
Created at: March 20, 2026, 1:04 p.m.