Triple

T3574237
Position Surface form Disambiguated ID Type / Status
Subject President of Albania E75647 entity
Predicate seat P75 FINISHED
Object Tirana E33263 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: Tirana | Statement: [President of Albania, seat, Tirana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tirana
Context triple: [President of Albania, seat, Tirana]
  • A. Tirana chosen
    Tirana is the capital and largest city of Albania, serving as its political, economic, and cultural center in the Balkans.
  • 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. Pristina
    Pristina is the capital and largest city of Kosovo, serving as its political, economic, and cultural center in the central Balkans.
  • D. 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.
  • E. Prizren
    Prizren is a historic and culturally rich city in southern Kosovo, known for its well-preserved Ottoman-era architecture and diverse religious heritage.
  • 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_69ad85d5e3008190bdfe0bacdd1f5a1b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0d928f08190830347b3b032178a completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bbc077048190917260402e2ccf66 completed March 13, 2026, 7:24 a.m.
Created at: March 8, 2026, 3:21 p.m.