Triple

T4300962
Position Surface form Disambiguated ID Type / Status
Subject Norfolk International Airport E99834 entity
Predicate IATAcode P418 FINISHED
Object ORF
ORF is the three-letter IATA airport code for Norfolk International Airport in Norfolk, Virginia.
 E428666 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: ORF | Statement: [Norfolk International Airport, IATAcode, ORF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ORF
Context triple: [Norfolk International Airport, IATAcode, ORF]
  • A. ORF
    ORF is Austria's national public service broadcaster, operating multiple television and radio channels as well as online services.
  • B. ORC
    ORC (Optimized Row Columnar) is a highly efficient, columnar storage file format commonly used in big data systems to enable fast analytics and compression.
  • C. ORC
    ORC is the abbreviation for the Organized Reserve Corps, a former component of the United States Army Reserve structure.
  • D. ORAP
    ORAP is the standard legal citation abbreviation for the Oregon Rules of Appellate Procedure, which govern practice in Oregon’s appellate courts.
  • E. OFR
    OFR is a U.S. Treasury Department bureau that collects and analyzes financial data to support oversight of the stability of the financial system.
  • 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: ORF
Triple: [Norfolk International Airport, IATAcode, ORF]
Generated description
ORF is the three-letter IATA airport code for Norfolk International Airport in Norfolk, Virginia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ORF
Target entity description: ORF is the three-letter IATA airport code for Norfolk International Airport in Norfolk, Virginia.
  • A. ORF
    ORF is Austria's national public service broadcaster, operating multiple television and radio channels as well as online services.
  • B. ORC
    ORC is the abbreviation for the Organized Reserve Corps, a former component of the United States Army Reserve structure.
  • C. ORC
    ORC (Optimized Row Columnar) is a highly efficient, columnar storage file format commonly used in big data systems to enable fast analytics and compression.
  • D. ORAP
    ORAP is the standard legal citation abbreviation for the Oregon Rules of Appellate Procedure, which govern practice in Oregon’s appellate courts.
  • E. OFR
    OFR is a U.S. Treasury Department bureau that collects and analyzes financial data to support oversight of the stability of the financial system.
  • 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.