Triple

T13462458
Position Surface form Disambiguated ID Type / Status
Subject Maykop E311405 entity
Predicate hasAirport P105 FINISHED
Object Maykop Airport
Maykop Airport is a regional civil airport serving the city of Maykop in the Republic of Adygea, Russia.
E1041619 NE FINISHED

How this triple was built (4 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: Maykop Airport | Statement: [Maykop, hasAirport, Maykop Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maykop Airport
Context triple: [Maykop, hasAirport, Maykop Airport]
  • A. Barnaul Airport
    Barnaul Airport is a regional airport in Barnaul, Russia, serving as a key air gateway for the Altai Krai region with domestic and limited international flights.
  • B. Baratayevka Airport
    Baratayevka Airport is a regional airport serving the city of Ulyanovsk in Russia.
  • C. Nalchik Airport
    Nalchik Airport is a regional civil airport serving the city of Nalchik in the Kabardino-Balkaria Republic of Russia, handling domestic flights and connecting the area to major Russian destinations.
  • D. Nadym Airport
    Nadym Airport is a regional airport in Nadym, Russia, primarily serving as a key base for operations in the Yamalo-Nenets Autonomous Okrug.
  • E. Grabtsevo Airport
    Grabtsevo Airport is the main commercial airport serving the city of Kaluga in western Russia, providing regional and limited international air connections.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Maykop Airport
Triple: [Maykop, hasAirport, Maykop Airport]
Generated description
Maykop Airport is a regional civil airport serving the city of Maykop in the Republic of Adygea, Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maykop Airport
Target entity description: Maykop Airport is a regional civil airport serving the city of Maykop in the Republic of Adygea, Russia.
  • A. Barnaul Airport
    Barnaul Airport is a regional airport in Barnaul, Russia, serving as a key air gateway for the Altai Krai region with domestic and limited international flights.
  • B. Baratayevka Airport
    Baratayevka Airport is a regional airport serving the city of Ulyanovsk in Russia.
  • C. Nalchik Airport
    Nalchik Airport is a regional civil airport serving the city of Nalchik in the Kabardino-Balkaria Republic of Russia, handling domestic flights and connecting the area to major Russian destinations.
  • D. Nadym Airport
    Nadym Airport is a regional airport in Nadym, Russia, primarily serving as a key base for operations in the Yamalo-Nenets Autonomous Okrug.
  • E. Grabtsevo Airport
    Grabtsevo Airport is the main commercial airport serving the city of Kaluga in western Russia, providing regional and limited international air connections.
  • F. None of above. chosen

Provenance (5 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf0d95fc81909d9f73d5315dc7b4 completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f739a2c75c819093765eb9d0d2377e completed May 3, 2026, 12:03 p.m.
NEDg Description generation batch_69f73db030ec8190a7d6b2cb1a3d52ed completed May 3, 2026, 12:21 p.m.
NED2 Entity disambiguation (via description) batch_69f73e8531a48190a280407f291d004c completed May 3, 2026, 12:24 p.m.
Created at: April 9, 2026, 9:41 p.m.