Triple

T12775453
Position Surface form Disambiguated ID Type / Status
Subject Kikaijima E305356 entity
Predicate hasAirport P105 FINISHED
Object Kikai Airport
Kikai Airport is a small regional airport in Kagoshima Prefecture, Japan, serving the island of Kikaijima with domestic flights.
E1024204 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: Kikai Airport | Statement: [Kikaijima, hasAirport, Kikai Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kikai Airport
Context triple: [Kikaijima, hasAirport, Kikai Airport]
  • A. Makung Airport
    Makung Airport is a regional airport serving the Penghu Islands in Taiwan, providing domestic flights that connect the archipelago with major cities on the Taiwanese mainland.
  • B. Beni Airport
    Beni Airport is a small public airport serving the city of Beni in the North Kivu province of the Democratic Republic of the Congo.
  • C. Kadala Airport
    Kadala Airport is the main commercial airport serving the city of Chita in eastern Siberia, Russia.
  • D. Puyo Airport
    Puyo Airport is a regional public airport serving the city of Puyo and the surrounding area in Ecuador’s Amazonian Pastaza Province.
  • E. Kirakira Airport
    Kirakira Airport is a small regional airfield serving the town of Kirakira and surrounding communities in Makira-Ulawa Province of the Solomon Islands.
  • 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: Kikai Airport
Triple: [Kikaijima, hasAirport, Kikai Airport]
Generated description
Kikai Airport is a small regional airport in Kagoshima Prefecture, Japan, serving the island of Kikaijima with domestic flights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kikai Airport
Target entity description: Kikai Airport is a small regional airport in Kagoshima Prefecture, Japan, serving the island of Kikaijima with domestic flights.
  • A. Makung Airport
    Makung Airport is a regional airport serving the Penghu Islands in Taiwan, providing domestic flights that connect the archipelago with major cities on the Taiwanese mainland.
  • B. Beni Airport
    Beni Airport is a small public airport serving the city of Beni in the North Kivu province of the Democratic Republic of the Congo.
  • C. Kadala Airport
    Kadala Airport is the main commercial airport serving the city of Chita in eastern Siberia, Russia.
  • D. Puyo Airport
    Puyo Airport is a regional public airport serving the city of Puyo and the surrounding area in Ecuador’s Amazonian Pastaza Province.
  • E. Kirakira Airport
    Kirakira Airport is a small regional airfield serving the town of Kirakira and surrounding communities in Makira-Ulawa Province of the Solomon Islands.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df6b3c88190b0bbe70de8ddcbf3 completed April 10, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eac829ec8190bea8efdc93151aa0 completed May 3, 2026, 6:27 a.m.
NEDg Description generation batch_69f6ebb1cd208190970ad8c21e852d93 completed May 3, 2026, 6:31 a.m.
NED2 Entity disambiguation (via description) batch_69f6ec48035881909342b57c061a22a9 completed May 3, 2026, 6:33 a.m.
Created at: April 9, 2026, 5:29 p.m.