Triple

T18204135
Position Surface form Disambiguated ID Type / Status
Subject Hugging Face E435862 entity
Predicate notableProduct P1448 FINISHED
Object Inference API 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: Inference API | Statement: [Hugging Face, notableProduct, Inference API]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inference API
Context triple: [Hugging Face, notableProduct, Inference API]
  • A. SageMaker Real-time Inference
    SageMaker Real-time Inference is a managed Amazon SageMaker capability that lets you deploy machine learning models as always-on, low-latency APIs for real-time prediction workloads.
  • B. Goya inference processor
    The Goya inference processor is Habana Labs’ specialized AI chip designed to accelerate deep learning inference workloads with high performance and efficiency.
  • C. SageMaker Serverless Inference
    SageMaker Serverless Inference is an AWS machine learning deployment option that automatically provisions and scales compute resources to host models for inference without requiring users to manage servers or infrastructure.
  • D. OpenAI API platform
    The OpenAI API platform is a cloud-based service that provides developers with programmatic access to OpenAI’s language, code, and other AI models for integration into applications and workflows.
  • E. NVIDIA inference platform
    The NVIDIA inference platform is a comprehensive suite of hardware and software tools designed to accelerate and optimize AI model deployment and real-time inference across data center, edge, and embedded environments.
  • 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: Inference API
Target entity description: Inference API is Hugging Face’s cloud-based service that lets developers run and scale machine learning models via simple API calls without managing their own infrastructure.
  • A. SageMaker Real-time Inference
    SageMaker Real-time Inference is a managed Amazon SageMaker capability that lets you deploy machine learning models as always-on, low-latency APIs for real-time prediction workloads.
  • B. Goya inference processor
    The Goya inference processor is Habana Labs’ specialized AI chip designed to accelerate deep learning inference workloads with high performance and efficiency.
  • C. SageMaker Serverless Inference
    SageMaker Serverless Inference is an AWS machine learning deployment option that automatically provisions and scales compute resources to host models for inference without requiring users to manage servers or infrastructure.
  • D. OpenAI API platform
    The OpenAI API platform is a cloud-based service that provides developers with programmatic access to OpenAI’s language, code, and other AI models for integration into applications and workflows.
  • E. NVIDIA inference platform
    The NVIDIA inference platform is a comprehensive suite of hardware and software tools designed to accelerate and optimize AI model deployment and real-time inference across data center, edge, and embedded environments.
  • 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_69d8b90dba6481908e119eb9aa4ca0cb completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e221bbbc819088a7559a46b7d4e7 completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.