Triple

T15870790
Position Surface form Disambiguated ID Type / Status
Subject Poso E384823 entity
Predicate nearbyAirport P350 FINISHED
Object Kasiguncu Airport
Kasiguncu Airport is a regional airport serving the town of Poso in Central Sulawesi, Indonesia.
E1190486 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: Kasiguncu Airport | Statement: [Poso, nearbyAirport, Kasiguncu Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kasiguncu Airport
Context triple: [Poso, nearbyAirport, Kasiguncu Airport]
  • A. Sibulan Airport
    Sibulan Airport is a domestic airport serving Dumaguete and the surrounding areas in Negros Oriental, in the Central Visayas region of the Philippines.
  • B. Pakyong Airport
    Pakyong Airport is a domestic airport in the Indian state of Sikkim that serves as the primary air gateway to the region’s capital and surrounding Himalayan areas.
  • C. Gizo Airport
    Gizo Airport is a small regional airfield serving the town of Gizo and surrounding areas in the Western Province of the Solomon Islands.
  • D. Loakan Airport
    Loakan Airport is a small domestic airport serving the city of Baguio in the mountainous Cordillera region of the 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: Kasiguncu Airport
Triple: [Poso, nearbyAirport, Kasiguncu Airport]
Generated description
Kasiguncu Airport is a regional airport serving the town of Poso in Central Sulawesi, Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kasiguncu Airport
Target entity description: Kasiguncu Airport is a regional airport serving the town of Poso in Central Sulawesi, Indonesia.
  • A. Sibulan Airport
    Sibulan Airport is a domestic airport serving Dumaguete and the surrounding areas in Negros Oriental, in the Central Visayas region of the Philippines.
  • B. Pakyong Airport
    Pakyong Airport is a domestic airport in the Indian state of Sikkim that serves as the primary air gateway to the region’s capital and surrounding Himalayan areas.
  • C. Gizo Airport
    Gizo Airport is a small regional airfield serving the town of Gizo and surrounding areas in the Western Province of the Solomon Islands.
  • D. Loakan Airport
    Loakan Airport is a small domestic airport serving the city of Baguio in the mountainous Cordillera region of the 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e155f915788190a8efc3b3380cb829 completed April 16, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbbff15c81909cb148a33b51a16e completed May 10, 2026, 1:13 a.m.
NEDg Description generation batch_69ffdc813208819088519396fa5298a6 completed May 10, 2026, 1:16 a.m.
NED2 Entity disambiguation (via description) batch_69ffdced694c8190a196ae36e5d6a99e completed May 10, 2026, 1:18 a.m.
Created at: April 10, 2026, 4:50 a.m.