Triple

T18205377
Position Surface form Disambiguated ID Type / Status
Subject AutoConfig E435887 entity
Predicate readsFrom P43634 FINISHED
Object Hugging Face Hub NE NERFINISHED

How this triple was built (2 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: Hugging Face Hub | Statement: [AutoConfig, readsFrom, Hugging Face Hub]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hugging Face Hub
Context triple: [AutoConfig, readsFrom, Hugging Face Hub]
  • A. Hugging Face chosen
    Hugging Face is an AI company and open-source community best known for its tools and libraries that make it easy to build, share, and deploy state-of-the-art machine learning models.
  • B. Hugging Face Transformers
    Hugging Face Transformers is a widely used open-source library that provides state-of-the-art transformer-based models and tools for natural language processing and related machine learning tasks.
  • C. Hugging Face Datasets
    Hugging Face Datasets is an open-source library that provides a large collection of ready-to-use datasets and efficient data loading tools for machine learning and natural language processing workflows.
  • D. TensorFlow Hub
    TensorFlow Hub is a library and online repository of reusable machine learning models and components designed to simplify sharing and deploying pretrained models in TensorFlow applications.
  • E. Hugging Face Accelerate
    Hugging Face Accelerate is a lightweight library that simplifies running and scaling PyTorch and Transformers models across CPUs, GPUs, and distributed hardware with minimal code changes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69e4e2234b988190bbe2c2164d61f65f completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.