Triple

T18204559
Position Surface form Disambiguated ID Type / Status
Subject DeBERTa E435870 entity
Predicate benchmark P17142 FINISHED
Object SuperGLUE — 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: SuperGLUE | Statement: [DeBERTa, benchmark, SuperGLUE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SuperGLUE
Context triple: [DeBERTa, benchmark, SuperGLUE]
  • A. 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.
  • B. Longformer
    Longformer is a transformer-based neural network architecture designed for efficient processing of very long sequences using sparse attention mechanisms.
  • C. DeepScale
    DeepScale was an AI startup focused on efficient deep learning and computer vision models for resource-constrained devices, particularly in the automotive and embedded systems space.
  • D. 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.
  • 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: SuperGLUE
Target entity description: SuperGLUE is a challenging benchmark suite of diverse natural language understanding tasks designed to evaluate and compare the performance of advanced language models.
  • A. 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.
  • B. Longformer
    Longformer is a transformer-based neural network architecture designed for efficient processing of very long sequences using sparse attention mechanisms.
  • C. DeepScale
    DeepScale was an AI startup focused on efficient deep learning and computer vision models for resource-constrained devices, particularly in the automotive and embedded systems space.
  • D. 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.
  • 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)

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_69e4e222831081908f7d5500424e3acb completed April 19, 2026, 2:09 p.m.
Created at: April 10, 2026, 10:32 a.m.