Triple

T7114624
Position Surface form Disambiguated ID Type / Status
Subject Sofia Airport E165787 entity
Predicate operator P179 FINISHED
Object Sofia Airport EAD E165787 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: Sofia Airport EAD | Statement: [Sofia Airport, operator, Sofia Airport EAD]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sofia Airport EAD
Context triple: [Sofia Airport, operator, Sofia Airport EAD]
  • A. Sofia Airport chosen
    Sofia Airport is the main international airport serving Bulgaria’s capital city, Sofia, and one of the country’s busiest air transport hubs.
  • B. Varna Airport
    Varna Airport is an international airport serving the city of Varna and the surrounding Black Sea resort region in Bulgaria.
  • C. Platov International Airport
    Platov International Airport is a major modern airport serving the city of Rostov-on-Don and the surrounding region in southern Russia.
  • D. Rota International Airport
    Rota International Airport is a public airport serving the island of Rota in the Northern Mariana Islands, providing regional air connections within the western Pacific.
  • E. Burgas Airport
    Burgas Airport is an international airport on Bulgaria’s Black Sea coast that serves the city of Burgas and nearby seaside resorts.
  • 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.