Triple

T15182832
Position Surface form Disambiguated ID Type / Status
Subject RBG E362787 entity
Predicate identifies P310 FINISHED
Object Air Arabia Egypt E74125 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: Air Arabia Egypt | Statement: [RBG, identifies, Air Arabia Egypt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Air Arabia Egypt
Context triple: [RBG, identifies, Air Arabia Egypt]
  • A. Air Arabia Egypt chosen
    Air Arabia Egypt is an Egyptian low-cost airline based in Alexandria that operates regional and international flights as part of the Air Arabia Group.
  • B. Air Arabia
    Air Arabia is a low-cost airline based in the United Arab Emirates, known for operating budget-friendly flights across the Middle East, North Africa, Asia, and Europe.
  • C. Afriqiyah Airways
    Afriqiyah Airways is a Libyan state-owned airline based in Tripoli that operates scheduled passenger services across Africa, Europe, and the Middle East.
  • D. Air Arabia Maroc
    Air Arabia Maroc is a Moroccan low-cost airline based in Casablanca that operates regional and international flights as part of the Air Arabia Group.
  • E. Israir Airlines
    Israir Airlines is an Israeli airline that operates domestic and international flights, primarily serving leisure and tourist destinations from its base in Israel.
  • 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_69d85a09a39c81908759f23268e2d408 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006663ad48190986b680001be0e9b completed April 15, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd2a2eb48190a569847d2f583c61 completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 3:09 a.m.