Triple
T18204367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XLNet |
E435866
|
entity |
| Predicate | achievedStateOfTheArtOn |
P1518
|
FINISHED |
| Object | GLUE benchmark |
—
|
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: GLUE benchmark | Statement: [XLNet, achievedStateOfTheArtOn, GLUE benchmark]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GLUE benchmark Context triple: [XLNet, achievedStateOfTheArtOn, GLUE benchmark]
-
A.
Hugging Face
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.
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.
-
D.
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.
-
E.
Longformer
Longformer is a transformer-based neural network architecture designed for efficient processing of very long sequences using sparse attention mechanisms.
- 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: GLUE benchmark Target entity description: The GLUE benchmark is a widely used collection of natural language understanding tasks designed to evaluate and compare the performance of language models.
-
A.
Hugging Face
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.
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.
-
D.
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.
-
E.
Longformer
Longformer is a transformer-based neural network architecture designed for efficient processing of very long sequences using sparse attention mechanisms.
- 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.