Triple

T16405571
Position Surface form Disambiguated ID Type / Status
Subject Malaysian airport network E398415 entity
Predicate hasComponent P35 FINISHED
Object Limbang Airport
Limbang Airport is a regional public airport serving the town of Limbang in northern Sarawak, Malaysia, providing domestic connections within the country’s Bornean region.
E1237998 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: Limbang Airport | Statement: [Malaysian airport network, hasComponent, Limbang Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limbang Airport
Context triple: [Malaysian airport network, hasComponent, Limbang Airport]
  • A. Pangsuma Airport
    Pangsuma Airport is a regional airport serving the town of Putussibau in West Kalimantan, Indonesia.
  • B. Mutiara Airport
    Mutiara Airport is a public airport in Palu, Central Sulawesi, Indonesia, serving as the main air gateway to the region.
  • C. Jumandy Airport
    Jumandy Airport is a regional airport serving the city of Tena and the surrounding Amazonian area in Ecuador.
  • D. Borongan Airport
    Borongan Airport is a domestic airport serving the city of Borongan and surrounding areas in Eastern Samar, Philippines.
  • E. Dumatubin Airport
    Dumatubin Airport is a small regional airport serving the Kai Islands in Indonesia, providing domestic air connections to this remote archipelago.
  • 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: Limbang Airport
Triple: [Malaysian airport network, hasComponent, Limbang Airport]
Generated description
Limbang Airport is a regional public airport serving the town of Limbang in northern Sarawak, Malaysia, providing domestic connections within the country’s Bornean region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Limbang Airport
Target entity description: Limbang Airport is a regional public airport serving the town of Limbang in northern Sarawak, Malaysia, providing domestic connections within the country’s Bornean region.
  • A. Pangsuma Airport
    Pangsuma Airport is a regional airport serving the town of Putussibau in West Kalimantan, Indonesia.
  • B. Mutiara Airport
    Mutiara Airport is a public airport in Palu, Central Sulawesi, Indonesia, serving as the main air gateway to the region.
  • C. Jumandy Airport
    Jumandy Airport is a regional airport serving the city of Tena and the surrounding Amazonian area in Ecuador.
  • D. Borongan Airport
    Borongan Airport is a domestic airport serving the city of Borongan and surrounding areas in Eastern Samar, Philippines.
  • E. Dumatubin Airport
    Dumatubin Airport is a small regional airport serving the Kai Islands in Indonesia, providing domestic air connections to this remote archipelago.
  • 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_6a00c291e2008190b41a989c5c6e2860 completed May 10, 2026, 5:38 p.m.
NEDg Description generation batch_6a00c332051c8190b086a6e29b8d9c61 completed May 10, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_6a00c434d8f88190a71c1c4c8e475e33 completed May 10, 2026, 5:45 p.m.
Created at: April 10, 2026, 5:09 a.m.