Triple

T4300963
Position Surface form Disambiguated ID Type / Status
Subject Norfolk International Airport E99834 entity
Predicate ICAOcode P419 FINISHED
Object KORF
KORF is the ICAO airport code for Norfolk International Airport, a major commercial airport serving the Hampton Roads region of Virginia, USA.
 E428667 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: KORF | Statement: [Norfolk International Airport, ICAOcode, KORF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: KORF
Context triple: [Norfolk International Airport, ICAOcode, KORF]
  • A. KORL
    KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
  • B. Kors
    Kors is the surname of American fashion designer Michael Kors, known for his eponymous luxury brand.
  • C. Kok-boru
    Kok-boru is a traditional Central Asian horseback team game, similar to polo, in which riders compete to carry and score with a goat or sheep carcass.
  • D. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • E. KO
    KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
  • 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: KORF
Triple: [Norfolk International Airport, ICAOcode, KORF]
Generated description
KORF is the ICAO airport code for Norfolk International Airport, a major commercial airport serving the Hampton Roads region of Virginia, USA.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: KORF
Target entity description: KORF is the ICAO airport code for Norfolk International Airport, a major commercial airport serving the Hampton Roads region of Virginia, USA.
  • A. KORL
    KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
  • B. Kors
    Kors is the surname of American fashion designer Michael Kors, known for his eponymous luxury brand.
  • C. Kok-boru
    Kok-boru is a traditional Central Asian horseback team game, similar to polo, in which riders compete to carry and score with a goat or sheep carcass.
  • D. RKC
    RKC is the commonly used abbreviation for the Revised Kyoto Convention, an international agreement that standardizes and simplifies customs procedures worldwide.
  • E. KO
    KO is the New York Stock Exchange ticker symbol for The Coca-Cola Company, one of the world’s largest and most recognizable beverage corporations.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3509fb2b88190a13ab88a5b924052 completed March 12, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c74d59688190820cef42c4228a3a completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c7bd187c8190b79894c864ea5b19 completed March 14, 2026, 8:40 p.m.
NED2 Entity disambiguation (via description) batch_69b5c88035dc8190beacf43974a29c78 completed March 14, 2026, 8:43 p.m.
Created at: March 12, 2026, 11:08 p.m.