Triple

T823098
Position Surface form Disambiguated ID Type / Status
Subject Gaziantep E17791 entity
Predicate hasAirport P105 FINISHED
Object Oğuzeli Airport
Oğuzeli Airport is the main public airport serving the city and province of Gaziantep in southeastern Turkey.
E99642 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: Oğuzeli Airport | Statement: [Gaziantep, hasAirport, Oğuzeli Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oğuzeli Airport
Context triple: [Gaziantep, hasAirport, Oğuzeli Airport]
  • A. Konya Airport
    Konya Airport is a combined civil and military airport serving the city of Konya in central Turkey.
  • B. Bursa Yenişehir Airport
    Bursa Yenişehir Airport is a regional airport in Turkey serving the city of Bursa with domestic and limited international flights.
  • C. Adnan Menderes Airport
    Adnan Menderes Airport is the main international airport serving the city of Izmir and the surrounding Aegean region of Turkey.
  • D. Sabiha Gokcen International Airport
    Sabiha Gokcen International Airport is Istanbul’s secondary international airport on the Asian side of the city, serving as a major hub for low-cost and regional flights.
  • E. Esenboğa International Airport
    Esenboğa International Airport is the main international airport serving Turkey’s capital city, Ankara, handling both domestic and international flights.
  • 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: Oğuzeli Airport
Triple: [Gaziantep, hasAirport, Oğuzeli Airport]
Generated description
Oğuzeli Airport is the main public airport serving the city and province of Gaziantep in southeastern Turkey.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Oğuzeli Airport
Target entity description: Oğuzeli Airport is the main public airport serving the city and province of Gaziantep in southeastern Turkey.
  • A. Konya Airport
    Konya Airport is a combined civil and military airport serving the city of Konya in central Turkey.
  • B. Bursa Yenişehir Airport
    Bursa Yenişehir Airport is a regional airport in Turkey serving the city of Bursa with domestic and limited international flights.
  • C. Adnan Menderes Airport
    Adnan Menderes Airport is the main international airport serving the city of Izmir and the surrounding Aegean region of Turkey.
  • D. Sabiha Gokcen International Airport
    Sabiha Gokcen International Airport is Istanbul’s secondary international airport on the Asian side of the city, serving as a major hub for low-cost and regional flights.
  • E. Esenboğa International Airport
    Esenboğa International Airport is the main international airport serving Turkey’s capital city, Ankara, handling both domestic and international flights.
  • 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_69a4937bcaac8190a322524ac6f45a5a completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4ab7c139c8190b6d75661b5138d89 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a79291d51c81908163024842300a6e completed March 4, 2026, 2:01 a.m.
NEDg Description generation batch_69a795676ce881909d93a50841dcc054 completed March 4, 2026, 2:13 a.m.
NED2 Entity disambiguation (via description) batch_69a795cd74a88190b858e29eb86527a9 completed March 4, 2026, 2:15 a.m.
Created at: March 1, 2026, 7:38 p.m.