Triple

T18204132
Position Surface form Disambiguated ID Type / Status
Subject Hugging Face E435862 entity
Predicate notableProduct P1448 FINISHED
Object PEFT library — 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: PEFT library | Statement: [Hugging Face, notableProduct, PEFT library]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PEFT library
Context triple: [Hugging Face, notableProduct, PEFT library]
  • A. 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.
  • B. Megatron-LM
    Megatron-LM is a large-scale language model training framework developed by NVIDIA, designed to efficiently train massive transformer models through model, tensor, and pipeline parallelism.
  • C. DeepSpeed
    DeepSpeed is a deep learning optimization library from Microsoft that enables efficient, large-scale training of models across distributed GPU systems.
  • D. DeBERTa
    DeBERTa is a transformer-based language model developed by Microsoft that improves upon BERT and RoBERTa using disentangled attention and enhanced mask decoder mechanisms for superior natural language understanding.
  • E. RoBERTa
    RoBERTa is a robustly optimized transformer-based language model developed by Facebook AI that improves upon BERT through enhanced training strategies and larger-scale data.
  • 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: PEFT library
Target entity description: The PEFT library is a Hugging Face toolkit that enables efficient fine-tuning of large language models using parameter-efficient techniques such as LoRA and adapters.
  • A. 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.
  • B. Megatron-LM
    Megatron-LM is a large-scale language model training framework developed by NVIDIA, designed to efficiently train massive transformer models through model, tensor, and pipeline parallelism.
  • C. DeepSpeed
    DeepSpeed is a deep learning optimization library from Microsoft that enables efficient, large-scale training of models across distributed GPU systems.
  • D. DeBERTa
    DeBERTa is a transformer-based language model developed by Microsoft that improves upon BERT and RoBERTa using disentangled attention and enhanced mask decoder mechanisms for superior natural language understanding.
  • E. RoBERTa
    RoBERTa is a robustly optimized transformer-based language model developed by Facebook AI that improves upon BERT through enhanced training strategies and larger-scale data.
  • 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.