Triple

T18799684
Position Surface form Disambiguated ID Type / Status
Subject Mayavi E459728 entity
Predicate usesLibrary P4791 FINISHED
Object VTK
VTK (the Visualization Toolkit) is an open-source software system for 3D computer graphics, image processing, and scientific visualization.
 E956222 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: VTK | Statement: [Mayavi, usesLibrary, VTK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: VTK
Context triple: [Mayavi, usesLibrary, VTK]
  • A. ITK
    ITK is the national Inuit organization in Canada that represents and advocates for Inuit rights and interests at the federal level.
  • B. VMD
    VMD is the acronym for the Veterinary Medicines Directorate, the UK government agency responsible for regulating veterinary medicines and promoting animal health and welfare.
  • C. Kitware
    Kitware is a software research and development company best known for creating open-source tools and platforms for scientific computing, visualization, and software build management.
  • D. Mayavi
    Mayavi is a 3D scientific data visualization library for Python, widely used for interactive plotting and analysis of complex numerical data.
  • E. OSG
    OSG is the abbreviated name commonly used to refer to the Office of the Secretary-General.
  • 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: VTK
Triple: [Mayavi, usesLibrary, VTK]
Generated description
VTK (the Visualization Toolkit) is an open-source software system for 3D computer graphics, image processing, and scientific visualization.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: VTK
Target entity description: VTK (the Visualization Toolkit) is an open-source software system for 3D computer graphics, image processing, and scientific visualization.
  • A. ITK
    ITK is the national Inuit organization in Canada that represents and advocates for Inuit rights and interests at the federal level.
  • B. VMD
    VMD is the acronym for the Veterinary Medicines Directorate, the UK government agency responsible for regulating veterinary medicines and promoting animal health and welfare.
  • C. Kitware chosen
    Kitware is a software research and development company best known for creating open-source tools and platforms for scientific computing, visualization, and software build management.
  • D. Mayavi
    Mayavi is a 3D scientific data visualization library for Python, widely used for interactive plotting and analysis of complex numerical data.
  • E. OSG
    OSG is the abbreviated name commonly used to refer to the Office of the Secretary-General.
  • F. None of above.

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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a02273b481909bc250144a0ace32 completed April 20, 2026, 3:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a055bbcb2508190a651701c4a56252f completed May 14, 2026, 5:21 a.m.
NEDg Description generation batch_6a055fe446948190a67cc8bcd93cd587 completed May 14, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_6a056034b0ac8190b5bf66ec10e70dce completed May 14, 2026, 5:40 a.m.
Created at: April 10, 2026, 11:53 a.m.