Triple

T18204455
Position Surface form Disambiguated ID Type / Status
Subject BART E435868 entity
Predicate hasVariant P455 FINISHED
Object MBART — 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: MBART | Statement: [BART, hasVariant, MBART]

Disambiguation candidates (1 decision)

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: MBART
Context triple: [BART, hasVariant, MBART]
  • A. mBART chosen
    mBART is a multilingual sequence-to-sequence Transformer model designed for tasks like machine translation and text generation across many languages.
  • B. 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.
  • C. 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.
  • D. XLNet
    XLNet is a generalized autoregressive pretraining model for natural language processing that improves on BERT by leveraging permutation-based language modeling to better capture bidirectional context.
  • 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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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.