Triple

T6956988
Position Surface form Disambiguated ID Type / Status
Subject Garner Field Airport E161268 entity
Predicate IATAcode P418 FINISHED
Object UVA
UVA is the three-letter IATA airport code assigned to Garner Field Airport in Uvalde, Texas.
 E631190 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: UVA | Statement: [Garner Field Airport, IATAcode, UVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UVA
Context triple: [Garner Field Airport, IATAcode, UVA]
  • A. UVA
    UVA is the University of Virginia, a major public research university in Charlottesville known for its strong academics and NCAA Division I athletic programs.
  • B. UVa
    UVa is the commonly used abbreviation for the historic Spanish public institution the University of Valladolid.
  • C. Uva
    Uva is a historical region in Sri Lanka that formed part of the Kandyan Kingdom and is known for its mountainous terrain and tea-growing highlands.
  • D. UCA
    UCA is a Jesuit-run Central American University in Managua, Nicaragua, known for its strong emphasis on social justice, human rights, and critical scholarship.
  • E. UCA
    UCA is a Spanish public university based in Cádiz, known for its programs in marine sciences, engineering, and humanities.
  • 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: UVA
Triple: [Garner Field Airport, IATAcode, UVA]
Generated description
UVA is the three-letter IATA airport code assigned to Garner Field Airport in Uvalde, Texas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UVA
Target entity description: UVA is the three-letter IATA airport code assigned to Garner Field Airport in Uvalde, Texas.
  • A. UVA
    UVA is the University of Virginia, a major public research university in Charlottesville known for its strong academics and NCAA Division I athletic programs.
  • B. UVa
    UVa is the commonly used abbreviation for the historic Spanish public institution the University of Valladolid.
  • C. Uva
    Uva is a historical region in Sri Lanka that formed part of the Kandyan Kingdom and is known for its mountainous terrain and tea-growing highlands.
  • D. UCA
    UCA is a Jesuit-run Central American University in Managua, Nicaragua, known for its strong emphasis on social justice, human rights, and critical scholarship.
  • E. UCA
    UCA is a Spanish public university based in Cádiz, known for its programs in marine sciences, engineering, and humanities.
  • 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dad0e52081908b524dc6a66bab01 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7588e2c5c8190a66a0205f3c2bf99 completed March 28, 2026, 4:26 a.m.
NEDg Description generation batch_69c7598d785881909a79ec6be6546a1c completed March 28, 2026, 4:31 a.m.
NED2 Entity disambiguation (via description) batch_69c75a0b33788190a120c42f901ac56e completed March 28, 2026, 4:33 a.m.
Created at: March 27, 2026, 2:29 p.m.