Triple

T8146874
Position Surface form Disambiguated ID Type / Status
Subject Tunoshna Airport E190232 entity
Predicate ICAOcode P419 FINISHED
Object UUDL
UUDL is the ICAO airport code for Tunoshna Airport, a regional airport serving the Yaroslavl area in Russia.
E712366 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: UUDL | Statement: [Tunoshna Airport, ICAOcode, UUDL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UUDL
Context triple: [Tunoshna Airport, ICAOcode, UUDL]
  • A. UUDD
    UUDD is the ICAO airport code for Moscow’s Domodedovo International Airport, one of Russia’s major aviation hubs.
  • B. UL
    UL is the two-letter IATA airline designator assigned to SriLankan Airlines, the flag carrier of Sri Lanka.
  • C. UL
    UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
  • D. UL
    UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
  • E. UDDF
    UDDF (Universal Dive Data Format) is an open, XML-based standard for storing and exchanging scuba dive profile and configuration data between dive computers, software, and logging tools.
  • 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: UUDL
Triple: [Tunoshna Airport, ICAOcode, UUDL]
Generated description
UUDL is the ICAO airport code for Tunoshna Airport, a regional airport serving the Yaroslavl area in Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: UUDL
Target entity description: UUDL is the ICAO airport code for Tunoshna Airport, a regional airport serving the Yaroslavl area in Russia.
  • A. UUDD
    UUDD is the ICAO airport code for Moscow’s Domodedovo International Airport, one of Russia’s major aviation hubs.
  • B. UL
    UL is the vehicle registration code used on license plates for the city of Ulm in Germany.
  • C. UL
    UL is the two-letter IATA airline designator assigned to SriLankan Airlines, the flag carrier of Sri Lanka.
  • D. UL
    UL is the New York Stock Exchange ticker symbol for Unilever, a major multinational consumer goods company known for its food, personal care, and household products.
  • E. UDDF
    UDDF (Universal Dive Data Format) is an open, XML-based standard for storing and exchanging scuba dive profile and configuration data between dive computers, software, and logging tools.
  • 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_69ca82be7ba8819087de0147e9292c83 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb447d6b1881908ff3fa25af6b4e80 completed March 31, 2026, 3:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc94b667d88190a0b47c7e0e07f338 completed April 1, 2026, 3:44 a.m.
NEDg Description generation batch_69cc95c228c08190a603c1dff44ff299 completed April 1, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69cc96b02d38819085eb51c1943b3045 completed April 1, 2026, 3:53 a.m.
Created at: March 30, 2026, 5:36 p.m.