Triple

T7790965
Position Surface form Disambiguated ID Type / Status
Subject Maio E180176 entity
Predicate transport P230 FINISHED
Object Maio Airport
Maio Airport is a small public airport serving the island of Maio in Cape Verde, providing domestic air connections to the rest of the archipelago.
E693803 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: Maio Airport | Statement: [Maio, transport, Maio Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maio Airport
Context triple: [Maio, transport, Maio Airport]
  • A. 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.
  • B. Moruya Airport
    Moruya Airport is a regional airport in New South Wales, Australia, providing air transport services for the town of Moruya and the surrounding Eurobodalla region.
  • C. Gando Airport
    Gando Airport is the main international airport serving Gran Canaria in Spain’s Canary Islands.
  • D. Osubi Airport
    Osubi Airport is a domestic airport serving the city of Warri and its surrounding region in Delta State, Nigeria.
  • E. Katunayake Airport
    Katunayake Airport, now known as Bandaranaike International Airport, is the main international gateway to Sri Lanka located near Colombo.
  • 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: Maio Airport
Triple: [Maio, transport, Maio Airport]
Generated description
Maio Airport is a small public airport serving the island of Maio in Cape Verde, providing domestic air connections to the rest of the archipelago.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maio Airport
Target entity description: Maio Airport is a small public airport serving the island of Maio in Cape Verde, providing domestic air connections to the rest of the archipelago.
  • A. 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.
  • B. Moruya Airport
    Moruya Airport is a regional airport in New South Wales, Australia, providing air transport services for the town of Moruya and the surrounding Eurobodalla region.
  • C. Gando Airport
    Gando Airport is the main international airport serving Gran Canaria in Spain’s Canary Islands.
  • D. Osubi Airport
    Osubi Airport is a domestic airport serving the city of Warri and its surrounding region in Delta State, Nigeria.
  • E. Katunayake Airport
    Katunayake Airport, now known as Bandaranaike International Airport, is the main international gateway to Sri Lanka located near Colombo.
  • 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_69ca827d22208190b4dc5aa680edcf5d completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cae9375dcc8190a6cb696c02aeceb7 completed March 30, 2026, 9:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb13b38e708190a688ce4effbf7c48 completed March 31, 2026, 12:22 a.m.
NEDg Description generation batch_69cb1636b0d48190a57c2d3a7b3b41ed completed March 31, 2026, 12:32 a.m.
NED2 Entity disambiguation (via description) batch_69cb1a29d2988190bb64aada0d2ef463 completed March 31, 2026, 12:49 a.m.
Created at: March 30, 2026, 4:30 p.m.