Triple

T20722629
Position Surface form Disambiguated ID Type / Status
Subject Vukovar-Srijem County E509355 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object VU
VU is the vehicle registration code used on license plates for vehicles registered in Vukovar-Srijem County, Croatia.
 E1446632 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: VU | Statement: [Vukovar-Srijem County, hasVehicleRegistrationCode, VU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VU
Context triple: [Vukovar-Srijem County, hasVehicleRegistrationCode, VU]
  • A. 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.
  • 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. 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: VU
Triple: [Vukovar-Srijem County, hasVehicleRegistrationCode, VU]
Generated description
VU is the vehicle registration code used on license plates for vehicles registered in Vukovar-Srijem County, Croatia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VU
Target entity description: VU is the vehicle registration code used on license plates for vehicles registered in Vukovar-Srijem County, Croatia.
  • A. 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.
  • B. VUT
    VUT is the Czech abbreviation for Brno University of Technology, a major technical and engineering university based in Brno, Czech Republic.
  • C. VUT
    VUT is the three-letter ISO 3166-1 alpha-3 country code assigned to Vanuatu.
  • 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. 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_69e0b4c4cc648190b45fda6e2b20af56 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c1d6bdcc8190ba42c44159a2c0d5 completed April 21, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a08e05734d88190b6386afc9e2e2d12 completed May 16, 2026, 9:23 p.m.
NEDg Description generation batch_6a08e101997881909ad7ed5e91cf1ed7 completed May 16, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_6a08e1ba6cf08190a43b1d57ef061a72 completed May 16, 2026, 9:29 p.m.
Created at: April 16, 2026, 12:27 p.m.