Triple

T10060982
Position Surface form Disambiguated ID Type / Status
Subject Tolmachevo Airport E212986 entity
Predicate ICAOcode P419 FINISHED
Object UNNT
UNNT is the ICAO airport code for Tolmachevo Airport, the main international airport serving Novosibirsk in Russia.
 E838833 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: UNNT | Statement: [Tolmachevo Airport, ICAOcode, UNNT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UNNT
Context triple: [Tolmachevo Airport, ICAOcode, UNNT]
  • A. UNNC
    UNNC is the University of Nottingham Ningbo China, a Sino-foreign joint university located in Ningbo, Zhejiang Province, offering British-style higher education in China.
  • B. UNN
    UNN is the commonly used acronym for the University of Nigeria, Nsukka, one of Nigeria’s leading federal universities.
  • C. UNT
    UNT is the commonly used acronym for the National University of Trujillo, a public higher education institution in Trujillo, Peru.
  • D. UNTL
    UNTL is the main public university of Timor-Leste, offering higher education and research across a range of academic disciplines.
  • E. NNU
    NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
  • 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: UNNT
Triple: [Tolmachevo Airport, ICAOcode, UNNT]
Generated description
UNNT is the ICAO airport code for Tolmachevo Airport, the main international airport serving Novosibirsk in Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UNNT
Target entity description: UNNT is the ICAO airport code for Tolmachevo Airport, the main international airport serving Novosibirsk in Russia.
  • A. UNNC
    UNNC is the University of Nottingham Ningbo China, a Sino-foreign joint university located in Ningbo, Zhejiang Province, offering British-style higher education in China.
  • B. UNN
    UNN is the commonly used acronym for the University of Nigeria, Nsukka, one of Nigeria’s leading federal universities.
  • C. UNT
    UNT is the commonly used acronym for the National University of Trujillo, a public higher education institution in Trujillo, Peru.
  • D. UNTL
    UNTL is the main public university of Timor-Leste, offering higher education and research across a range of academic disciplines.
  • E. NNU
    NNU is a comprehensive public university in Nanjing, China, known for its strong programs in teacher education, humanities, and sciences.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcfd1fc98819082ec3f2f91151955 completed April 2, 2026, 2:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a6779348190ab8db058fb6e5ce1 completed April 5, 2026, 5:22 p.m.
NEDg Description generation batch_69d29c76b84081909e23944c792aecbd completed April 5, 2026, 5:31 p.m.
NED2 Entity disambiguation (via description) batch_69d29ce64bf0819089e8ab126e33180e completed April 5, 2026, 5:33 p.m.
Created at: March 30, 2026, 8:57 p.m.