Triple

T21953719
Position Surface form Disambiguated ID Type / Status
Subject SVV E542129 entity
Predicate abbreviation P43 FINISHED
Object SVV NE NERFINISHED

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: SVV | Statement: [SVV, abbreviation, SVV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SVV
Context triple: [SVV, abbreviation, SVV]
  • A. SVV chosen
    SVV is the abbreviation for the Norwegian Public Roads Administration, the national authority responsible for planning, building, operating, and maintaining Norway’s public road network.
  • B. SSV
    SSV is a lightweight, off-road side-by-side vehicle class commonly used in rally raid competitions for its agility and versatility over rough terrain.
  • C. VVSS
    VVSS (Vertical Volute Spring Suspension) is an early U.S. tank suspension system using vertical volute springs to support and cushion tracked armored vehicles.
  • D. VVI
    VVI is the IATA airport code for Viru Viru International Airport, the main international gateway serving Santa Cruz de la Sierra, Bolivia.
  • E. VV
    VV is the common abbreviation for VistaVision, a high-resolution widescreen 35mm motion picture film format developed by Paramount Pictures in the 1950s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47ef0e48190a50e1bcc43f4b3fd completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f1243dfb4081909bc7a722843ffea7 completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:59 p.m.