Triple

T18204469
Position Surface form Disambiguated ID Type / Status
Subject BART E435868 entity
Predicate openSourceImplementation P7052 FINISHED
Object Fairseq — NE NERFINISHED

Named-entity recognition

Before disambiguation, gpt-5-mini classified whether the object phrase is a named entity — the step behind the object's NE type shown above.

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: Fairseq | Statement: [BART, openSourceImplementation, Fairseq]

Disambiguation candidates (2 decisions)

The exact options the model was shown at each disambiguation step, with the option it chose highlighted — the evidence behind this triple's disambiguated ids.

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fairseq
Context triple: [BART, openSourceImplementation, Fairseq]
  • A. Wav2Vec2
    Wav2Vec2 is a self-supervised deep learning model for automatic speech recognition that learns powerful audio representations directly from raw waveforms.
  • B. Transformer-XL
    Transformer-XL is a neural network architecture for language modeling that extends the Transformer with segment-level recurrence and relative positional encodings to better capture long-range dependencies.
  • C. 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.
  • D. HuBERT
    HuBERT is a self-supervised speech representation learning model that learns powerful audio features from unlabeled speech for tasks like automatic speech recognition and audio classification.
  • E. 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.
  • 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: Fairseq
Target entity description: Fairseq is a Facebook AI Research (FAIR) sequence modeling toolkit for training and evaluating state-of-the-art neural networks for tasks like machine translation, summarization, and language modeling.
  • A. Wav2Vec2
    Wav2Vec2 is a self-supervised deep learning model for automatic speech recognition that learns powerful audio representations directly from raw waveforms.
  • B. Transformer-XL
    Transformer-XL is a neural network architecture for language modeling that extends the Transformer with segment-level recurrence and relative positional encodings to better capture long-range dependencies.
  • C. 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.
  • D. HuBERT
    HuBERT is a self-supervised speech representation learning model that learns powerful audio features from unlabeled speech for tasks like automatic speech recognition and audio classification.
  • E. 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.
  • F. None of above. chosen

Provenance (2 batches)

Stage Batch ID Job type Status
creating batch_69d8b90dba6481908e119eb9aa4ca0cb elicitation completed
NER batch_69e4e222831081908f7d5500424e3acb ner completed
Created at: April 10, 2026, 10:32 a.m.