Triple

T3453675
Position Surface form Disambiguated ID Type / Status
Subject Kandahar E72850 entity
Predicate hasLandmark P105 FINISHED
Object Kandahar International Airport E359353 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: Kandahar International Airport | Statement: [Kandahar, hasLandmark, Kandahar International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kandahar International Airport
Context triple: [Kandahar, hasLandmark, Kandahar International Airport]
  • A. Kandahar International Airport chosen
    Kandahar International Airport is a major airport in southern Afghanistan that serves both civilian flights and military operations.
  • B. Hamid Karzai International Airport
    Hamid Karzai International Airport is the main international airport serving Kabul and the primary air gateway to Afghanistan.
  • C. Dalbandin Airport
    Dalbandin Airport is a small domestic airport serving the town of Dalbandin in Balochistan, Pakistan, providing regional air connectivity.
  • D. Shah Makhdum Airport
    Shah Makhdum Airport is a regional domestic airport serving the city of Rajshahi in western Bangladesh.
  • E. Quetta International Airport
    Quetta International Airport is the main domestic and international air gateway serving the city of Quetta and the surrounding region of Balochistan, Pakistan.
  • 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_69ad85b12a908190a1d10a6b03b4f8ae completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbaa457fc8190824ca00254e962f9 completed March 8, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373a7da208190a8a9ad5ede8d4f0f completed March 13, 2026, 2:17 a.m.
Created at: March 8, 2026, 3:16 p.m.