Triple

T8686028
Position Surface form Disambiguated ID Type / Status
Subject Varna Free University E206160 entity
Predicate abbreviation P43 FINISHED
Object VFU
VFU is the commonly used abbreviation for Varna Free University, a private higher education institution in Varna, Bulgaria.
 E751345 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: VFU | Statement: [Varna Free University, abbreviation, VFU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VFU
Context triple: [Varna Free University, abbreviation, VFU]
  • A. VF
    VF is the IATA airline designator assigned to AJet, a Turkish low-cost carrier.
  • B. VFA
    VFA is the commonly used abbreviation for the Victorian Football Association, a historic Australian rules football competition based in the state of Victoria.
  • C. FV
    FV is the IATA airline designator assigned to Rossiya Airlines, a Russian carrier based in Saint Petersburg.
  • D. FVBU
    FVBU is the ICAO airport code for Joshua Mqabuko Nkomo International Airport in Bulawayo, Zimbabwe.
  • E. VU
    VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
  • 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: VFU
Triple: [Varna Free University, abbreviation, VFU]
Generated description
VFU is the commonly used abbreviation for Varna Free University, a private higher education institution in Varna, Bulgaria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VFU
Target entity description: VFU is the commonly used abbreviation for Varna Free University, a private higher education institution in Varna, Bulgaria.
  • A. VF
    VF is the IATA airline designator assigned to AJet, a Turkish low-cost carrier.
  • B. VFA
    VFA is the commonly used abbreviation for the Victorian Football Association, a historic Australian rules football competition based in the state of Victoria.
  • C. FV
    FV is the IATA airline designator assigned to Rossiya Airlines, a Russian carrier based in Saint Petersburg.
  • D. FVBU
    FVBU is the ICAO airport code for Joshua Mqabuko Nkomo International Airport in Bulawayo, Zimbabwe.
  • E. VU
    VU is a major research university in Amsterdam, Netherlands, known for its wide range of academic programs and emphasis on interdisciplinary and socially engaged scholarship.
  • 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_69ca835379688190aa06b9d98e684d58 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc4aec1f8c8190a9ab1a73c2dbcd3c completed March 31, 2026, 10:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3cd888c81909fb1ece99988db36 completed April 2, 2026, 10:55 p.m.
NEDg Description generation batch_69cef521010081908815779c0bd2aac9 completed April 2, 2026, 11 p.m.
NED2 Entity disambiguation (via description) batch_69cef727ea088190bf40eaf5424ae864 completed April 2, 2026, 11:09 p.m.
Created at: March 30, 2026, 6:33 p.m.