Triple
T8823477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cuDNN |
E209958
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object |
PaddlePaddle
PaddlePaddle is an open-source deep learning platform developed by Baidu, designed for large-scale distributed training and deployment of neural networks.
|
E760429
|
NE FINISHED |
How this triple was built (4 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: PaddlePaddle | Statement: [cuDNN, usedBy, PaddlePaddle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PaddlePaddle Context triple: [cuDNN, usedBy, PaddlePaddle]
-
A.
PyTorch
PyTorch is an open-source deep learning framework widely used for building and training neural networks, known for its dynamic computation graph and strong support for research and production in Python.
-
B.
MXNet
MXNet is an open-source deep learning framework designed for efficient, scalable training and inference across multiple GPUs and distributed systems.
-
C.
TensorFlow
TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
-
D.
NVIDIA TensorRT
NVIDIA TensorRT is a high-performance deep learning inference optimizer and runtime library designed to accelerate AI models on NVIDIA GPUs in production environments.
-
E.
CuPy
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: PaddlePaddle Triple: [cuDNN, usedBy, PaddlePaddle]
Generated description
PaddlePaddle is an open-source deep learning platform developed by Baidu, designed for large-scale distributed training and deployment of neural networks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PaddlePaddle Target entity description: PaddlePaddle is an open-source deep learning platform developed by Baidu, designed for large-scale distributed training and deployment of neural networks.
-
A.
PyTorch
PyTorch is an open-source deep learning framework widely used for building and training neural networks, known for its dynamic computation graph and strong support for research and production in Python.
-
B.
MXNet
MXNet is an open-source deep learning framework designed for efficient, scalable training and inference across multiple GPUs and distributed systems.
-
C.
TensorFlow
TensorFlow is an open-source, end-to-end machine learning and deep learning framework widely used for building, training, and deploying neural network models at scale.
-
D.
NVIDIA TensorRT
NVIDIA TensorRT is a high-performance deep learning inference optimizer and runtime library designed to accelerate AI models on NVIDIA GPUs in production environments.
-
E.
CuPy
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
- F. None of above. chosen
Provenance (5 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc6030b25081909d67488b35a72e05 |
completed | April 1, 2026, midnight |
| NED1 | Entity disambiguation (via context triple) | batch_69cf893e08b0819083c2d152d0f9c263 |
completed | April 3, 2026, 9:32 a.m. |
| NEDg | Description generation | batch_69cf8a3d8e548190911d44ee36875d44 |
completed | April 3, 2026, 9:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf8ae86e1881908a77f660c061bf69 |
completed | April 3, 2026, 9:39 a.m. |
Created at: March 30, 2026, 6:46 p.m.