Triple

T2923947
Position Surface form Disambiguated ID Type / Status
Subject Albanian Riviera E78798 entity
Predicate hasMajorSettlement P316 FINISHED
Object Vlorë E111395 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: Vlorë | Statement: [Albanian Riviera, hasMajorSettlement, Vlorë]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vlorë
Context triple: [Albanian Riviera, hasMajorSettlement, Vlorë]
  • A. Vlora chosen
    Vlora is a major coastal city and seaport in southwestern Albania, strategically located on the Adriatic Sea.
  • B. Gjirokastër
    Gjirokastër is a historic stone-built city in southern Albania, recognized as a UNESCO World Heritage Site for its well-preserved Ottoman-era architecture.
  • C. Durrës
    Durrës is a major port city on the Adriatic coast of Albania, historically significant as a strategic maritime gateway and one of the country’s oldest urban centers.
  • D. Prizren
    Prizren is a historic and culturally rich city in southern Kosovo, known for its well-preserved Ottoman-era architecture and diverse religious heritage.
  • E. Tirana
    Tirana is the capital and largest city of Albania, 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad97bf2df88190bd4f1e90d4656507 completed March 8, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b08664fe308190889e855821a32576 completed March 10, 2026, 9 p.m.
Created at: March 8, 2026, 2:55 p.m.