Triple

T15679809
Position Surface form Disambiguated ID Type / Status
Subject DAM E377539 entity
Predicate represents P129 FINISHED
Object Damascus International Airport E77907 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: Damascus International Airport | Statement: [DAM, represents, Damascus International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Damascus International Airport
Context triple: [DAM, represents, Damascus International Airport]
  • A. Damascus International Airport chosen
    Damascus International Airport is the main international gateway serving Syria’s capital, handling the majority of the country’s international air traffic.
  • B. Bassel Al-Assad International Airport
    Bassel Al-Assad International Airport is a major civilian and military airport in western Syria that serves the coastal city of Latakia and the surrounding region.
  • C. Al-Hasakah Airport
    Al-Hasakah Airport is a small regional airfield serving the city and surrounding region of Al-Hasakah in northeastern Syria.
  • D. Jowhar Airport
    Jowhar Airport is a public airfield serving the town of Jowhar in Somalia, providing regional air transport connections.
  • E. Al Ghaydah Airport
    Al Ghaydah Airport is a regional civilian airport serving the city of Al Ghaydah and the surrounding Mahra Governorate in eastern Yemen.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2f1640819086efd5a73bb9734a completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ee2a33c81908fcd120ca670b309 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:16 a.m.