Triple

T14138965
Position Surface form Disambiguated ID Type / Status
Subject University of Valencia E350371 entity
Predicate abbreviation P43 FINISHED
Object UVa
UVa is a Spanish public research university based in the city of Valencia, known for its wide range of academic programs and historical significance.
 E369128 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: [University of Valencia, abbreviation, UVa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UVa
Context triple: [University of Valencia, abbreviation, UVa]
  • A. UVa
    UVa is the commonly used abbreviation for the historic Spanish public institution the University of Valladolid.
  • B. UVA
    UVA is the three-letter IATA airport code assigned to Garner Field Airport in Uvalde, Texas.
  • C. 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.
  • D. UVM
    UVM is a public research university in Burlington, Vermont, known for its strong programs in environmental studies, agriculture, and the liberal arts.
  • E. ICPC
    ICPC is a standardized coding system used worldwide to classify patient data and clinical activity in primary care settings.
  • 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: [University of Valencia, abbreviation, UVa]
Generated description
UVa is a Spanish public research university based in the city of Valencia, known for its wide range of academic programs and historical significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UVa
Target entity description: UVa is a Spanish public research university based in the city of Valencia, known for its wide range of academic programs and historical significance.
  • A. UVa chosen
    UVa is the commonly used abbreviation for the historic Spanish public institution the University of Valladolid.
  • B. UVA
    UVA is the three-letter IATA airport code assigned to Garner Field Airport in Uvalde, Texas.
  • C. 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.
  • D. UVM
    UVM is a public research university in Burlington, Vermont, known for its strong programs in environmental studies, agriculture, and the liberal arts.
  • E. ICPC
    ICPC is a standardized coding system used worldwide to classify patient data and clinical activity in primary care settings.
  • F. None of above.

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_69d827865f608190b311820428ae027b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6111a36081909beff35c88a56960 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf16079c819080a74cd8a6eb37a6 completed May 7, 2026, 6:51 p.m.
NEDg Description generation batch_69fce89cf5b08190a2a610f49a4b6f90 completed May 7, 2026, 7:31 p.m.
NED2 Entity disambiguation (via description) batch_69fce984be2881909b38e3d9e4fac243 completed May 7, 2026, 7:35 p.m.
Created at: April 10, 2026, 12:40 a.m.