Triple

T12938924
Position Surface form Disambiguated ID Type / Status
Subject Vlora County E309587 entity
Predicate largestCity P235 FINISHED
Object Vlora 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: Vlora | Statement: [Vlora County, largestCity, Vlora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vlora
Context triple: [Vlora County, largestCity, Vlora]
  • A. Vlora chosen
    Vlora is a major coastal city and seaport in southwestern Albania, strategically located on the Adriatic Sea.
  • B. 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.
  • C. Sarandë
    Sarandë is a coastal city in southern Albania on the Ionian Sea, known for its beaches, tourism, and proximity to the UNESCO World Heritage site of Butrint.
  • D. Lezhë
    Lezhë is a historic town in northwestern Albania, known as the site of the League of Lezhë and for its cultural and archaeological heritage.
  • E. Elbasan
    Elbasan is a city in central Albania known as an important industrial and transportation hub with historical roots dating back to the Ottoman era.
  • 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_69d7bdfa933c8190b5a27aa4a08a19b7 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97dc8c0848190946e109ec98e4479 completed April 10, 2026, 10:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6fefdd3d8819091196f68c2fd5ad0 completed May 3, 2026, 7:53 a.m.
Created at: April 9, 2026, 5:43 p.m.