Triple

T4064748
Position Surface form Disambiguated ID Type / Status
Subject Virginia Landmarks Register E86297 entity
Predicate hasAbbreviation P43 FINISHED
Object VLR
VLR is the abbreviation for the Virginia Landmarks Register, the Commonwealth of Virginia’s official list of historically significant properties and districts.
 E410086 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: VLR | Statement: [Virginia Landmarks Register, hasAbbreviation, VLR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VLR
Context triple: [Virginia Landmarks Register, hasAbbreviation, VLR]
  • A. VL
    VL is the vehicle registration code used on license plates for vehicles registered in Râmnicu Vâlcea, Romania.
  • B. VLL
    VLL is the three-letter IATA airport code for Valladolid Airport in Spain.
  • C. VRA
    VRA is the common abbreviation for the landmark U.S. federal law enacted in 1965 to prohibit racial discrimination in voting.
  • D. VLG
    VLG is the ICAO airline designator used to identify Vueling, a Spanish low-cost carrier based in Barcelona.
  • E. VZ
    VZ is the stock ticker symbol for Verizon Communications Inc., a major U.S.-based telecommunications company providing wireless, internet, and related services.
  • 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: VLR
Triple: [Virginia Landmarks Register, hasAbbreviation, VLR]
Generated description
VLR is the abbreviation for the Virginia Landmarks Register, the Commonwealth of Virginia’s official list of historically significant properties and districts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VLR
Target entity description: VLR is the abbreviation for the Virginia Landmarks Register, the Commonwealth of Virginia’s official list of historically significant properties and districts.
  • A. VL
    VL is the vehicle registration code used on license plates for vehicles registered in Râmnicu Vâlcea, Romania.
  • B. VLL
    VLL is the three-letter IATA airport code for Valladolid Airport in Spain.
  • C. VRA
    VRA is the common abbreviation for the landmark U.S. federal law enacted in 1965 to prohibit racial discrimination in voting.
  • D. VLG
    VLG is the ICAO airline designator used to identify Vueling, a Spanish low-cost carrier based in Barcelona.
  • E. VZ
    VZ is the stock ticker symbol for Verizon Communications Inc., a major U.S.-based telecommunications company providing wireless, internet, and related services.
  • 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_69aed93c69208190a4efac0efe3cd69b completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbf44c888190b5746d93e9f8e3a3 completed March 9, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562ae949c819092affaaca97c16d1 completed March 14, 2026, 1:29 p.m.
NEDg Description generation batch_69b5633103e081909dbe7a7e54877343 completed March 14, 2026, 1:31 p.m.
NED2 Entity disambiguation (via description) batch_69b563eca17c81908deff0d361a7be87 completed March 14, 2026, 1:34 p.m.
Created at: March 9, 2026, 3:38 p.m.