Triple

T7936980
Position Surface form Disambiguated ID Type / Status
Subject Model Driven Architecture E184309 entity
Predicate usesConcept P531 FINISHED
Object MOF E699639 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: MOF | Statement: [Model Driven Architecture, usesConcept, MOF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MOF
Context triple: [Model Driven Architecture, usesConcept, MOF]
  • A. MOF
    MOF is the commonly used abbreviation for Japan’s Ministry of Finance, the government body responsible for national fiscal and economic policy.
  • B. MOF chosen
    MOF (Meta-Object Facility) is a standard framework defined by the Object Management Group for specifying, constructing, and managing technology-neutral metamodels in model-driven engineering.
  • C. MFO
    MFO is an international peacekeeping organization that supervises the implementation of the security provisions of the Egypt–Israel peace treaty in the Sinai Peninsula.
  • D. MOSIF
    MOSIF is an alternative name associated with BepiColombo, the joint ESA–JAXA mission to study the planet Mercury.
  • E. Mol
    Mol is a municipality in the Belgian region of Flanders known for its lakes, nature reserves, and recreational tourism.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3aef2394819086eea1f6ab117aed completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe019a094819082baecdcb007c84f completed March 31, 2026, 2:54 p.m.
Created at: March 30, 2026, 5:08 p.m.