Triple

T17601495
Position Surface form Disambiguated ID Type / Status
Subject Mosspark E428711 entity
Predicate hasStationCode P1289 FINISHED
Object MPK NE NERFINISHED

How this triple was built (3 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: MPK | Statement: [Mosspark, hasStationCode, MPK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MPK
Context triple: [Mosspark, hasStationCode, MPK]
  • A. MPK21
    MPK21 is a major office building on Meta’s Menlo Park campus, known for its expansive, park-like rooftop and open-plan workspace designed to foster collaboration.
  • B. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • C. MPS
    MPS (Metal Performance Shaders) is an Apple framework that provides highly optimized GPU-accelerated compute and graphics shaders for tasks like image processing and machine learning on Apple devices.
  • D. MPS
    MPS is the central government agency responsible for public security, policing, and domestic law enforcement in the People's Republic of China.
  • E. MPS
    MPS is a language workbench and integrated development environment by JetBrains designed for creating and working with domain-specific languages using projectional editing.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: MPK
Target entity description: MPK is the National Rail station code for Mosspark railway station in Glasgow, Scotland.
  • A. MPK21
    MPK21 is a major office building on Meta’s Menlo Park campus, known for its expansive, park-like rooftop and open-plan workspace designed to foster collaboration.
  • B. MPS
    MPS is the central government agency responsible for public security, policing, and domestic law enforcement in the People's Republic of China.
  • C. MPS
    MPS is a leading German research institute specializing in the study of the Sun and the solar system, operating under the Max Planck Society.
  • D. MPS
    MPS is a language workbench and integrated development environment by JetBrains designed for creating and working with domain-specific languages using projectional editing.
  • E. MPS
    MPS (Metal Performance Shaders) is an Apple framework that provides highly optimized GPU-accelerated compute and graphics shaders for tasks like image processing and machine learning on Apple devices.
  • F. None of above. chosen

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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c48dfc08190ba360e6082cffa87 completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.