Triple

T11127783
Position Surface form Disambiguated ID Type / Status
Subject Al Aqiq E263192 entity
Predicate transportInfrastructure P1777 FINISHED
Object Al Aqiq Airport E905761 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: Al Aqiq Airport | Statement: [Al Aqiq, transportInfrastructure, Al Aqiq Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Al Aqiq Airport
Context triple: [Al Aqiq, transportInfrastructure, Al Aqiq Airport]
  • A. Al Aqiq Airport chosen
    Al Aqiq Airport is a regional airport in the Al Aqiq area of Saudi Arabia that serves local air travel needs.
  • B. Al Aroui Airport
    Al Aroui Airport is the main commercial airport serving the city and region of Nador in northeastern Morocco.
  • C. Gardabya Airport
    Gardabya Airport is a Libyan airport serving the coastal city of Sirte and its surrounding region.
  • D. Sania Ramel Airport
    Sania Ramel Airport is a regional airport serving the city of Tétouan in northern Morocco, providing domestic and limited international flights.
  • E. Taif Regional Airport
    Taif Regional Airport is a public airport serving the city of Taif and surrounding areas in western Saudi Arabia, handling both domestic and limited international flights.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e830e804819097fcc3826d84dab8 completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441dcb4608190a4cfa46c194d11ae completed April 19, 2026, 2:45 a.m.
Created at: April 8, 2026, 9:28 p.m.