Triple
T816376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NumPy |
E17659
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object |
CuPy
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
|
E97065
|
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: CuPy | Statement: [NumPy, influenced, CuPy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CuPy Context triple: [NumPy, influenced, CuPy]
-
A.
NumPy
NumPy is a fundamental Python library that provides efficient multi-dimensional arrays and numerical computing tools widely used in scientific computing and data analysis.
-
B.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
-
C.
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.
-
D.
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.
-
E.
SciPy
SciPy is an open-source Python library that provides advanced scientific and technical computing tools, including modules for optimization, integration, statistics, signal processing, and linear algebra.
- 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: CuPy Triple: [NumPy, influenced, CuPy]
Generated description
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CuPy Target entity description: CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
-
A.
NumPy
NumPy is a fundamental Python library that provides efficient multi-dimensional arrays and numerical computing tools widely used in scientific computing and data analysis.
-
B.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
-
C.
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.
-
D.
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.
-
E.
SciPy
SciPy is an open-source Python library that provides advanced scientific and technical computing tools, including modules for optimization, integration, statistics, signal processing, and linear algebra.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab621d2c819083f10bff4f66c482 |
completed | March 1, 2026, 9:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d8d1a448190be8494fa2776615a |
completed | March 3, 2026, 11:23 p.m. |
| NEDg | Description generation | batch_69a78bd0a1d48190907434a17853dfb1 |
completed | March 4, 2026, 1:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a78c3a57d88190a994ed44bcb2d8d1 |
completed | March 4, 2026, 1:34 a.m. |
Created at: March 1, 2026, 7:38 p.m.