Triple

T19834504
Position Surface form Disambiguated ID Type / Status
Subject Nalchik Airport E476551 entity
Predicate hasCode P9567 FINISHED
Object NAL NE NERFINISHED

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: NAL | Statement: [Nalchik Airport, hasCode, NAL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: NAL
Context triple: [Nalchik Airport, hasCode, NAL]
  • A. NAL chosen
    NAL is the IATA airport code for Nalchik Airport, which serves the city of Nalchik in the Kabardino-Balkaria region of Russia.
  • B. NA
    NA is the commonly used abbreviation for the National Assembly of Pakistan, the lower house of the country's bicameral parliament.
  • C. NA
    The NA is the land warfare branch and largest component of the Nigerian Armed Forces, responsible for ground military operations and national defense.
  • D. NA
    NA is the commonly used abbreviation for the National Assembly of Namibia, the country's lower house of Parliament and primary legislative body.
  • E. NA
    NA is the commonly used abbreviation for the National Assembly of Laos, the country's unicameral legislative body.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51c7c188190b926f3a2a7b5f881 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e656d0e738819093000d3307962328 completed April 20, 2026, 4:39 p.m.
Created at: April 10, 2026, 1:50 p.m.