Triple

T8328276
Position Surface form Disambiguated ID Type / Status
Subject Queen’s Award for Voluntary Service E195009 entity
Predicate alsoKnownAs P39 FINISHED
Object QAVS
QAVS is a prestigious UK national honour that recognises outstanding voluntary groups for their exceptional service to local communities.
 E725293 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: QAVS | Statement: [Queen’s Award for Voluntary Service, alsoKnownAs, QAVS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: QAVS
Context triple: [Queen’s Award for Voluntary Service, alsoKnownAs, QAVS]
  • A. QVT
    QVT (Query/View/Transformation) is an OMG standard language for specifying model-to-model transformations in model-driven software engineering.
  • B. SVQ
    SVQ is the IATA airport code for Seville Airport, the main international airport serving Seville and the Andalusia region in southern Spain.
  • C. VQS
    VQS is the IATA airport code for Antonio Rivera Rodríguez Airport, which serves the island of Vieques in Puerto Rico.
  • D. XVQ
    XVQ is the IATA station code assigned to Venezia Santa Lucia, the main railway station in Venice, Italy.
  • E. The QC
    The QC is a popular nickname for Charlotte, North Carolina, reflecting its identity as a major financial and cultural hub in the southeastern United States.
  • 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: QAVS
Triple: [Queen’s Award for Voluntary Service, alsoKnownAs, QAVS]
Generated description
QAVS is a prestigious UK national honour that recognises outstanding voluntary groups for their exceptional service to local communities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: QAVS
Target entity description: QAVS is a prestigious UK national honour that recognises outstanding voluntary groups for their exceptional service to local communities.
  • A. QVT
    QVT (Query/View/Transformation) is an OMG standard language for specifying model-to-model transformations in model-driven software engineering.
  • B. SVQ
    SVQ is the IATA airport code for Seville Airport, the main international airport serving Seville and the Andalusia region in southern Spain.
  • C. VQS
    VQS is the IATA airport code for Antonio Rivera Rodríguez Airport, which serves the island of Vieques in Puerto Rico.
  • D. XVQ
    XVQ is the IATA station code assigned to Venezia Santa Lucia, the main railway station in Venice, Italy.
  • E. The QC
    The QC is a popular nickname for Charlotte, North Carolina, reflecting its identity as a major financial and cultural hub in the southeastern United States.
  • 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_69ca82e87f2c8190bdb71ee29dfc642d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f8243288190b1ae74d69395fc91 completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95c2c36481909793e9cd0c28168a completed April 1, 2026, 10:01 p.m.
NEDg Description generation batch_69cdab60ec308190a9001f9235e556b4 completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2e3457c8190a2d0cb6eeb81c9ef completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:56 p.m.