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.