Triple

T6986819
Position Surface form Disambiguated ID Type / Status
Subject Fuzhou Changle International Airport E161984 entity
Predicate IATACode P418 FINISHED
Object FOC
FOC is the IATA airport code for Fuzhou Changle International Airport, the main airport serving Fuzhou in Fujian Province, China.
 E633402 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: FOC | Statement: [Fuzhou Changle International Airport, IATACode, FOC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FOC
Context triple: [Fuzhou Changle International Airport, IATACode, FOC]
  • A. FOCs
    FOCs are rail freight operating companies in the United Kingdom that run cargo train services on the national rail network.
  • B. FOCAS
    FOCAS is an optical camera and spectrograph instrument used on the Subaru Telescope for detailed imaging and spectroscopic observations of astronomical objects.
  • C. FRO
    FRO is the three-letter ISO 3166-1 alpha-3 country code assigned to the Faroe Islands.
  • D. FOS
    FOS is a Hubble Space Telescope instrument designed to obtain spectra of very faint astronomical objects across a wide range of wavelengths.
  • E. FIO
    FIO is the acronym for the Federal Insurance Office, a U.S. Treasury Department agency that monitors the insurance industry and advises on national and international insurance policy.
  • 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: FOC
Triple: [Fuzhou Changle International Airport, IATACode, FOC]
Generated description
FOC is the IATA airport code for Fuzhou Changle International Airport, the main airport serving Fuzhou in Fujian Province, China.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FOC
Target entity description: FOC is the IATA airport code for Fuzhou Changle International Airport, the main airport serving Fuzhou in Fujian Province, China.
  • A. FOCs
    FOCs are rail freight operating companies in the United Kingdom that run cargo train services on the national rail network.
  • B. FOCAS
    FOCAS is an optical camera and spectrograph instrument used on the Subaru Telescope for detailed imaging and spectroscopic observations of astronomical objects.
  • C. FRO
    FRO is the three-letter ISO 3166-1 alpha-3 country code assigned to the Faroe Islands.
  • D. FOS
    FOS is a Hubble Space Telescope instrument designed to obtain spectra of very faint astronomical objects across a wide range of wavelengths.
  • E. FIO
    FIO is the acronym for the Federal Insurance Office, a U.S. Treasury Department agency that monitors the insurance industry and advises on national and international insurance policy.
  • 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_69c68856d7808190ab33ee914640281b completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db95c6148190bdb5f355ac04db3f completed March 27, 2026, 7:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c761cfda14819088e11889f0151a37 completed March 28, 2026, 5:06 a.m.
NEDg Description generation batch_69c7630440508190a66f218fd912d732 completed March 28, 2026, 5:11 a.m.
NED2 Entity disambiguation (via description) batch_69c7639747b88190b3429817d53c5703 completed March 28, 2026, 5:13 a.m.
Created at: March 27, 2026, 2:32 p.m.