Triple

T14932195
Position Surface form Disambiguated ID Type / Status
Subject Universidad de Viña del Mar E372293 entity
Predicate abbreviation P43 FINISHED
Object UVM
UVM is a private Chilean university located in Viña del Mar, known for offering a wide range of undergraduate and graduate programs.
 E1126866 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: UVM | Statement: [Universidad de Viña del Mar, abbreviation, UVM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UVM
Context triple: [Universidad de Viña del Mar, abbreviation, UVM]
  • A. UVM
    UVM is a public research university in Burlington, Vermont, known for its strong programs in environmental studies, agriculture, and the liberal arts.
  • B. UCT
    UCT is a leading public research university in Cape Town, South Africa, renowned as one of Africa’s top higher education institutions.
  • C. Uni
    Uni is an Etruscan goddess, broadly equivalent to the Roman Juno and Greek Hera, associated with marriage, fertility, and protection of the state.
  • D. Uni
    Uni is the commonly used nickname for University High School in Los Angeles, a public high school known for its diverse student body and long history on the Westside.
  • E. UVA
    UVA is the three-letter IATA airport code assigned to Garner Field Airport in Uvalde, Texas.
  • 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: UVM
Triple: [Universidad de Viña del Mar, abbreviation, UVM]
Generated description
UVM is a private Chilean university located in Viña del Mar, known for offering a wide range of undergraduate and graduate programs.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UVM
Target entity description: UVM is a private Chilean university located in Viña del Mar, known for offering a wide range of undergraduate and graduate programs.
  • A. UVM
    UVM is a public research university in Burlington, Vermont, known for its strong programs in environmental studies, agriculture, and the liberal arts.
  • B. UCT
    UCT is a leading public research university in Cape Town, South Africa, renowned as one of Africa’s top higher education institutions.
  • C. Uni
    Uni is an Etruscan goddess, broadly equivalent to the Roman Juno and Greek Hera, associated with marriage, fertility, and protection of the state.
  • D. Uni
    Uni is the commonly used nickname for University High School in Los Angeles, a public high school known for its diverse student body and long history on the Westside.
  • E. UVA
    UVA is the three-letter IATA airport code assigned to Garner Field Airport in Uvalde, Texas.
  • 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_69d85cc9da0c81908d583ca3f63a3908 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded646a0808190ba5c0c91bde011c5 completed April 15, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe72c86b5c81909e601a3fc78276bd completed May 8, 2026, 11:33 p.m.
NEDg Description generation batch_69fe7360c11481908e2e5127b466e31b completed May 8, 2026, 11:36 p.m.
NED2 Entity disambiguation (via description) batch_69fe743c37308190a045ef5f0ade8508 completed May 8, 2026, 11:39 p.m.
Created at: April 10, 2026, 2:37 a.m.