Triple
T9674940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MXNet |
E234123
|
entity |
| Predicate | supportsFeature |
P203
|
FINISHED |
| Object |
NDArray API
The NDArray API is MXNet’s core multi-dimensional array interface for efficient numerical computation and deep learning operations.
|
E814032
|
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: NDArray API | Statement: [MXNet, supportsFeature, NDArray API]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NDArray API Context triple: [MXNet, supportsFeature, NDArray API]
-
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.
tensor programs framework
The tensor programs framework is a theoretical approach developed by Greg Yang that rigorously analyzes and characterizes the behavior and scaling limits of large neural networks using tools from probability and random matrix theory.
-
C.
jax.experimental
jax.experimental is a submodule of the JAX library that provides access to experimental, unstable, or cutting-edge numerical and machine learning features not yet part of the stable API.
-
D.
CuPy
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
-
E.
ArrayComm
ArrayComm is a wireless communications technology company known for pioneering smart antenna and adaptive beamforming solutions to improve mobile network capacity and performance.
- 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: NDArray API Triple: [MXNet, supportsFeature, NDArray API]
Generated description
The NDArray API is MXNet’s core multi-dimensional array interface for efficient numerical computation and deep learning operations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NDArray API Target entity description: The NDArray API is MXNet’s core multi-dimensional array interface for efficient numerical computation and deep learning operations.
-
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.
tensor programs framework
The tensor programs framework is a theoretical approach developed by Greg Yang that rigorously analyzes and characterizes the behavior and scaling limits of large neural networks using tools from probability and random matrix theory.
-
C.
jax.experimental
jax.experimental is a submodule of the JAX library that provides access to experimental, unstable, or cutting-edge numerical and machine learning features not yet part of the stable API.
-
D.
CuPy
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
-
E.
ArrayComm
ArrayComm is a wireless communications technology company known for pioneering smart antenna and adaptive beamforming solutions to improve mobile network capacity and performance.
- 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_69ca848f55e48190b3f67252571c3d45 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c6d6dd48190a77c486337a58cb6 |
completed | April 1, 2026, 10:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18a2d030c8190ada52e855bc9afc8 |
completed | April 4, 2026, 10:01 p.m. |
| NEDg | Description generation | batch_69d18bf051448190aaa3a7198c23fd39 |
completed | April 4, 2026, 10:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d18c8783f08190858681b51096fe56 |
completed | April 4, 2026, 10:11 p.m. |
Created at: March 30, 2026, 8:15 p.m.