Triple

T13774581
Position Surface form Disambiguated ID Type / Status
Subject Guiuan E330970 entity
Predicate hasAirport P105 FINISHED
Object Guiuan Airport
Guiuan Airport is a small public airfield serving the municipality of Guiuan in Eastern Samar, Philippines, primarily handling domestic and general aviation flights.
E1068790 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: Guiuan Airport | Statement: [Guiuan, hasAirport, Guiuan Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guiuan Airport
Context triple: [Guiuan, hasAirport, Guiuan Airport]
  • A. Juanda International Airport
    Juanda International Airport is a major international airport serving the city of Surabaya and the surrounding East Java region in Indonesia.
  • B. Labasa Airport
    Labasa Airport is a small domestic airport serving the town of Labasa on the Fijian island of Vanua Levu.
  • C. Diffa Airport
    Diffa Airport is a small public airport serving the town and surrounding region of Diffa in southeastern Niger.
  • D. Iki Airport
    Iki Airport is a regional airport in Nagasaki Prefecture, Japan, providing air transport services to and from Iki Island.
  • E. 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.
  • 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: Guiuan Airport
Triple: [Guiuan, hasAirport, Guiuan Airport]
Generated description
Guiuan Airport is a small public airfield serving the municipality of Guiuan in Eastern Samar, Philippines, primarily handling domestic and general aviation flights.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Guiuan Airport
Target entity description: Guiuan Airport is a small public airfield serving the municipality of Guiuan in Eastern Samar, Philippines, primarily handling domestic and general aviation flights.
  • A. Juanda International Airport
    Juanda International Airport is a major international airport serving the city of Surabaya and the surrounding East Java region in Indonesia.
  • B. Labasa Airport
    Labasa Airport is a small domestic airport serving the town of Labasa on the Fijian island of Vanua Levu.
  • C. Diffa Airport
    Diffa Airport is a small public airport serving the town and surrounding region of Diffa in southeastern Niger.
  • D. Iki Airport
    Iki Airport is a regional airport in Nagasaki Prefecture, Japan, providing air transport services to and from Iki Island.
  • E. 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.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de023774b48190b19e43e87b94ba77 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c7007d5c8190800456e32101903f completed May 3, 2026, 10:06 p.m.
NEDg Description generation batch_69f7c8d477f881908f8cfd2783e7f10f completed May 3, 2026, 10:14 p.m.
NED2 Entity disambiguation (via description) batch_69f7ca27ffd4819080bccd6bfd88ddb3 completed May 3, 2026, 10:20 p.m.
Created at: April 9, 2026, 10:10 p.m.