Triple

T3808450
Position Surface form Disambiguated ID Type / Status
Subject King of the Albanians E93068 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: [King of the Albanians, seat, Tirana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tirana
Context triple: [King of the Albanians, 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80c7fc48190b5c2400918bba5c2 completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b503f3590c8190b18e2e9dfd84cbcd completed March 14, 2026, 6:45 a.m.
Created at: March 9, 2026, 3:16 p.m.