Triple

T20442108
Position Surface form Disambiguated ID Type / Status
Subject Academy of Fine Arts in Prague E501420 entity
Predicate shortName P43 FINISHED
Object AVU
AVU is the Academy of Fine Arts in Prague, a prestigious Czech institution dedicated to higher education and training in the visual arts.
E1431753 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: AVU | Statement: [Academy of Fine Arts in Prague, shortName, AVU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: AVU
Context triple: [Academy of Fine Arts in Prague, shortName, AVU]
  • A. AVST
    AVST is the stock ticker symbol for Avast, a cybersecurity company best known for its antivirus and internet security software.
  • B. AVC
    AVC is the U.S. State Department bureau responsible for overseeing arms control, nonproliferation, and verification and compliance with related international agreements.
  • C. AVC
    AVC is the personal technology and venture capital blog written by prominent venture capitalist Fred Wilson.
  • D. AV1
    AV1 is a royalty-free, next-generation video compression codec developed by the Alliance for Open Media to efficiently deliver high-quality video over the internet.
  • E. AVS
    AVS is a professional society focused on advancing the science and technology of materials, interfaces, and processing through research, education, and collaboration.
  • 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: AVU
Triple: [Academy of Fine Arts in Prague, shortName, AVU]
Generated description
AVU is the Academy of Fine Arts in Prague, a prestigious Czech institution dedicated to higher education and training in the visual arts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: AVU
Target entity description: AVU is the Academy of Fine Arts in Prague, a prestigious Czech institution dedicated to higher education and training in the visual arts.
  • A. AVST
    AVST is the stock ticker symbol for Avast, a cybersecurity company best known for its antivirus and internet security software.
  • B. AVC
    AVC is the U.S. State Department bureau responsible for overseeing arms control, nonproliferation, and verification and compliance with related international agreements.
  • C. AVC
    AVC is the personal technology and venture capital blog written by prominent venture capitalist Fred Wilson.
  • D. AV1
    AV1 is a royalty-free, next-generation video compression codec developed by the Alliance for Open Media to efficiently deliver high-quality video over the internet.
  • E. AVS
    AVS is a professional society focused on advancing the science and technology of materials, interfaces, and processing through research, education, and collaboration.
  • 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_69e0b4ab3cfc8190ac9bf32e932316b1 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e685f3b794819080745b135a305ba7 completed April 20, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0883ff8e6c8190b8699ea023e98799 completed May 16, 2026, 2:49 p.m.
NEDg Description generation batch_6a08860f244c81909f2602704a19b0c6 completed May 16, 2026, 2:58 p.m.
NED2 Entity disambiguation (via description) batch_6a08868eadd48190837d0fbefb3da02a completed May 16, 2026, 3 p.m.
Created at: April 16, 2026, 11:32 a.m.