Triple

T14402222
Position Surface form Disambiguated ID Type / Status
Subject Ministry of Finance of Finland E357098 entity
Predicate shortName P43 FINISHED
Object VM
VM is the commonly used abbreviation for Finland’s Ministry of Finance, the government body responsible for national economic and fiscal policy.
 E1097372 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: VM | Statement: [Ministry of Finance of Finland, shortName, VM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VM
Context triple: [Ministry of Finance of Finland, shortName, VM]
  • A. VM
    VM is the station code assigned to V. Mapa station in the Manila Light Rail Transit system.
  • B. VM
    VM is IBM's family of mainframe virtual machine operating systems designed to run multiple operating environments concurrently on System/370 and successor hardware.
  • C. VM
    VM is the abbreviation for the Volksmarine, the navy of the former German Democratic Republic (East Germany).
  • D. VMX
    VMX is a vector processing extension to the PowerPC architecture designed to accelerate multimedia, signal processing, and other parallelizable computations.
  • E. VMC
    VMC is the Venus Monitoring Camera, a wide-angle imaging instrument on the European Space Agency’s Venus Express spacecraft used to study Venus’s atmosphere and cloud dynamics.
  • 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: VM
Triple: [Ministry of Finance of Finland, shortName, VM]
Generated description
VM is the commonly used abbreviation for Finland’s Ministry of Finance, the government body responsible for national economic and fiscal policy.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VM
Target entity description: VM is the commonly used abbreviation for Finland’s Ministry of Finance, the government body responsible for national economic and fiscal policy.
  • A. VM
    VM is the abbreviation for the Volksmarine, the navy of the former German Democratic Republic (East Germany).
  • B. VM
    VM is IBM's family of mainframe virtual machine operating systems designed to run multiple operating environments concurrently on System/370 and successor hardware.
  • C. VM
    VM is the station code assigned to V. Mapa station in the Manila Light Rail Transit system.
  • D. VMX
    VMX is a vector processing extension to the PowerPC architecture designed to accelerate multimedia, signal processing, and other parallelizable computations.
  • E. VMC
    VMC is the Venus Monitoring Camera, a wide-angle imaging instrument on the European Space Agency’s Venus Express spacecraft used to study Venus’s atmosphere and cloud dynamics.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de908500048190bb6a20fe318d5c62 completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5520c07c8190bfdaf224dd779ced completed May 8, 2026, 3:14 a.m.
NEDg Description generation batch_69fd56bbd6e481909fd97f3808bc99fd completed May 8, 2026, 3:21 a.m.
NED2 Entity disambiguation (via description) batch_69fd5755156c8190bc27df83e940c403 completed May 8, 2026, 3:24 a.m.
Created at: April 10, 2026, 1:17 a.m.