Triple

T7114821
Position Surface form Disambiguated ID Type / Status
Subject Montenegro and the Littoral E165791 entity
Predicate seeCity P3207 FINISHED
Object Cetinje E144765 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: Cetinje | Statement: [Montenegro and the Littoral, seeCity, Cetinje]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cetinje
Context triple: [Montenegro and the Littoral, seeCity, Cetinje]
  • A. Cetinje chosen
    Cetinje is a historic town in Montenegro that served as the country’s old royal capital and cultural center.
  • B. Podgorica
    Podgorica is the capital and largest city of Montenegro, serving as its political, economic, and cultural center in the Balkans.
  • C. Pogradec
    Pogradec is a town in southeastern Albania known as a lakeside resort and cultural center on the shores of Lake Ohrid.
  • D. 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.
  • E. Smederevo
    Smederevo is a historic Serbian city on the Danube River, known for its large medieval fortress and role as a former capital of the Serbian Despotate.
  • 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_69c6888227bc8190a1394679e3116f90 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e5f0dab8819092103aefcaa1f9c2 completed March 27, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79cbfc7a08190ab07f3d65aa79f16 completed March 28, 2026, 9:17 a.m.
Created at: March 27, 2026, 2:43 p.m.