Triple

T5027135
Position Surface form Disambiguated ID Type / Status
Subject GCVO E113202 entity
Predicate precedenceOver P1616 FINISHED
Object MVO E113206 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: MVO | Statement: [GCVO, precedenceOver, MVO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MVO
Context triple: [GCVO, precedenceOver, MVO]
  • A. MVO chosen
    MVO is a post-nominal honorific indicating appointment as a Member of the Royal Victorian Order, a dynastic order of knighthood recognizing distinguished personal service to the British monarch.
  • B. MVA
    MVA is the state agency in Maryland responsible for driver licensing, vehicle registration, and related motor vehicle services.
  • C. MIV
    MIV is a specialized market segment of Borsa Italiana dedicated to the listing and trading of investment vehicles such as closed-end funds and investment companies.
  • D. MVRD
    MVRD is the commonly used acronym for the regional government district that encompasses the metropolitan area of Vancouver in British Columbia, Canada.
  • E. MVU
    MVU (Model-View-Update) is an architectural pattern for building user interfaces that emphasizes a unidirectional data flow, immutable state, and a clear separation between state, view rendering, and update logic.
  • 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_69bd443775e48190a646ffbfc4334723 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd738d852c8190a122354f1e1f5343 completed March 20, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c64db5c81909224c82ae9d9e0ab completed March 21, 2026, 1:25 p.m.
Created at: March 20, 2026, 1:36 p.m.