Triple

T16405589
Position Surface form Disambiguated ID Type / Status
Subject Malaysian airport network E398415 entity
Predicate hasComponent P35 FINISHED
Object Kapit Airport
Kapit Airport is a small regional airport in Sarawak, Malaysia, serving the town of Kapit and surrounding interior communities.
E1220257 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: Kapit Airport | Statement: [Malaysian airport network, hasComponent, Kapit Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kapit Airport
Context triple: [Malaysian airport network, hasComponent, Kapit Airport]
  • A. Iki Airport
    Iki Airport is a regional airport in Nagasaki Prefecture, Japan, providing air transport services to and from Iki Island.
  • B. Ramingining Airport
    Ramingining Airport is a small regional airfield serving the remote Aboriginal community of Ramingining in the Northern Territory of Australia.
  • C. Heho Airport
    Heho Airport is a regional airport in Myanmar that serves as the main air gateway to Taunggyi and the nearby Inle Lake area.
  • D. Whyalla Airport
    Whyalla Airport is a regional airport in South Australia that serves the city of Whyalla with domestic flights and general aviation services.
  • E. Katherine Airport
    Katherine Airport is a regional airport in the Northern Territory of Australia that serves the town of Katherine and its surrounding areas.
  • 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: Kapit Airport
Triple: [Malaysian airport network, hasComponent, Kapit Airport]
Generated description
Kapit Airport is a small regional airport in Sarawak, Malaysia, serving the town of Kapit and surrounding interior communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kapit Airport
Target entity description: Kapit Airport is a small regional airport in Sarawak, Malaysia, serving the town of Kapit and surrounding interior communities.
  • A. Iki Airport
    Iki Airport is a regional airport in Nagasaki Prefecture, Japan, providing air transport services to and from Iki Island.
  • B. Ramingining Airport
    Ramingining Airport is a small regional airfield serving the remote Aboriginal community of Ramingining in the Northern Territory of Australia.
  • C. Heho Airport
    Heho Airport is a regional airport in Myanmar that serves as the main air gateway to Taunggyi and the nearby Inle Lake area.
  • D. Whyalla Airport
    Whyalla Airport is a regional airport in South Australia that serves the city of Whyalla with domestic flights and general aviation services.
  • E. Katherine Airport
    Katherine Airport is a regional airport in the Northern Territory of Australia that serves the town of Katherine and its surrounding areas.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e327d2b4e48190b7153f198639e9cd completed April 18, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00679a900c8190aeb7a273943bf553 completed May 10, 2026, 11:10 a.m.
NEDg Description generation batch_6a00686f87408190b7d8a41cd54735d8 completed May 10, 2026, 11:13 a.m.
NED2 Entity disambiguation (via description) batch_6a006b6edd7081908730363b267253dd completed May 10, 2026, 11:26 a.m.
Created at: April 10, 2026, 5:09 a.m.