Triple

T14848827
Position Surface form Disambiguated ID Type / Status
Subject University of Vilnius E349172 entity
Predicate abbreviation P43 FINISHED
Object VU E58912 NE FINISHED

How this triple was built (2 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: VU | Statement: [University of Vilnius, abbreviation, VU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VU
Context triple: [University of Vilnius, abbreviation, VU]
  • A. VU chosen
    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.
  • B. VUT
    VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • C. VUT
    VUT is the Czech abbreviation for Brno University of Technology, a major technical and engineering university based in Brno, Czech Republic.
  • D. VKSU
    VKSU is a public university located in Ara, Bihar, India, offering undergraduate and postgraduate programs across various disciplines.
  • E. VSNU
    VSNU is the Association of Universities in the Netherlands, representing and coordinating the interests of Dutch research universities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded43eee188190bf24dc475b3abe28 completed April 14, 2026, 11:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe6504ac6081908074231cf628fd39 completed May 8, 2026, 10:34 p.m.
Created at: April 10, 2026, 1:53 a.m.