Triple

T18178613
Position Surface form Disambiguated ID Type / Status
Subject Tile IR E435224 entity
Predicate implementedInContextOf P86121 FINISHED
Object Vertex.AI PlaidML project 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: Vertex.AI PlaidML project | Statement: [Tile IR, implementedInContextOf, Vertex.AI PlaidML project]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vertex.AI PlaidML project
Context triple: [Tile IR, implementedInContextOf, Vertex.AI PlaidML project]
  • A. PlaidML
    PlaidML is an open-source, hardware-agnostic deep learning engine designed to accelerate neural network computation on a wide range of GPUs and other devices.
  • B. Vertex AI
    Vertex AI is Google Cloud’s unified machine learning platform for building, training, and deploying ML models at scale.
  • C. NVIDIA AI Workflows
    NVIDIA AI Workflows are pre-built, end-to-end AI pipelines from NVIDIA that streamline the development, deployment, and scaling of AI applications across common enterprise use cases.
  • D. Landing AI
    Landing AI is a technology company focused on making artificial intelligence accessible to traditional industries by helping them build and deploy practical AI solutions, particularly in manufacturing and computer vision.
  • E. Neptune ML
    Neptune ML is a machine learning capability for Amazon Neptune that enables users to build and run graph neural network models directly on graph data stored in the database.
  • 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: Vertex.AI PlaidML project
Target entity description: The Vertex.AI PlaidML project is an open-source machine learning compiler and runtime framework designed to optimize and run deep learning workloads efficiently across diverse hardware backends.
  • A. PlaidML chosen
    PlaidML is an open-source, hardware-agnostic deep learning engine designed to accelerate neural network computation on a wide range of GPUs and other devices.
  • B. Vertex AI
    Vertex AI is Google Cloud’s unified machine learning platform for building, training, and deploying ML models at scale.
  • C. NVIDIA AI Workflows
    NVIDIA AI Workflows are pre-built, end-to-end AI pipelines from NVIDIA that streamline the development, deployment, and scaling of AI applications across common enterprise use cases.
  • D. Landing AI
    Landing AI is a technology company focused on making artificial intelligence accessible to traditional industries by helping them build and deploy practical AI solutions, particularly in manufacturing and computer vision.
  • E. Neptune ML
    Neptune ML is a machine learning capability for Amazon Neptune that enables users to build and run graph neural network models directly on graph data stored in the database.
  • F. None of above.

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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4df5b68f081908aac8210270f1499 completed April 19, 2026, 1:57 p.m.
Created at: April 10, 2026, 10:31 a.m.