Triple

T10191423
Position Surface form Disambiguated ID Type / Status
Subject Cherepovets Airport E238043 entity
Predicate IATAcode P418 FINISHED
Object CEE
CEE is the IATA airport code for Cherepovets Airport, a regional airport serving the city of Cherepovets in Russia.
 E847489 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: CEE | Statement: [Cherepovets Airport, IATAcode, CEE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CEE
Context triple: [Cherepovets Airport, IATAcode, CEE]
  • A. CECS
    CECS is the commonly used abbreviation for the College of Engineering and Computer Science, an academic division focused on engineering and computing disciplines.
  • B. CCE
    CCE is a division at the California Institute of Technology focused on research and education in chemistry and chemical engineering.
  • C. CCE
    CCE is an abbreviation commonly used for the Center for Civic Engagement, an organization that promotes community involvement, public service, and civic responsibility.
  • D. CEC
    CEC is the primary state agency responsible for energy policy, planning, and regulation in California.
  • E. CEC
    CEC is the three-letter IATA airport code for Del Norte County Regional Airport in Crescent City, California.
  • 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: CEE
Triple: [Cherepovets Airport, IATAcode, CEE]
Generated description
CEE is the IATA airport code for Cherepovets Airport, a regional airport serving the city of Cherepovets in Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CEE
Target entity description: CEE is the IATA airport code for Cherepovets Airport, a regional airport serving the city of Cherepovets in Russia.
  • A. CECS
    CECS is the commonly used abbreviation for the College of Engineering and Computer Science, an academic division focused on engineering and computing disciplines.
  • B. CCE
    CCE is a division at the California Institute of Technology focused on research and education in chemistry and chemical engineering.
  • C. CCE
    CCE is an abbreviation commonly used for the Center for Civic Engagement, an organization that promotes community involvement, public service, and civic responsibility.
  • D. CEC
    CEC is the primary state agency responsible for energy policy, planning, and regulation in California.
  • E. CEC
    CEC is the three-letter IATA airport code for Del Norte County Regional Airport in Crescent City, California.
  • 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_69ca84de1b208190bf17bb305b002605 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded7eb1148190a2d175163685e233 completed April 2, 2026, 4:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69d317c0c22881909ed388721e80bafd completed April 6, 2026, 2:17 a.m.
NEDg Description generation batch_69d31b7fc66c8190b9de24200c149b45 completed April 6, 2026, 2:33 a.m.
NED2 Entity disambiguation (via description) batch_69d31c7bf1f88190beef483458923787 completed April 6, 2026, 2:37 a.m.
Created at: March 30, 2026, 9:13 p.m.