Triple
T9674961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MXNet |
E234123
|
entity |
| Predicate | previouslyDevelopedBy |
P85947
|
FINISHED |
| Object |
DMLC (Distributed Machine Learning Community)
DMLC (Distributed Machine Learning Community) is an open-source collaborative group that develops scalable machine learning and deep learning systems and tools, including major projects like Apache MXNet and XGBoost.
|
E814036
|
NE FINISHED |
How this triple was built (5 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: DMLC (Distributed Machine Learning Community) | Statement: [MXNet, previouslyDevelopedBy, DMLC (Distributed Machine Learning Community)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DMLC (Distributed Machine Learning Community) Context triple: [MXNet, previouslyDevelopedBy, DMLC (Distributed Machine Learning Community)]
-
A.
MXNet
MXNet is an open-source deep learning framework designed for efficient, scalable training and inference across multiple GPUs and distributed systems.
-
B.
PaddlePaddle
PaddlePaddle is an open-source deep learning platform developed by Baidu, designed for large-scale distributed training and deployment of neural networks.
-
C.
Microsoft Cognitive Toolkit
Microsoft Cognitive Toolkit (CNTK) is an open-source deep learning framework developed by Microsoft for building, training, and deploying neural networks at scale.
-
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.
NVIDIA RAPIDS
NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and analytics libraries designed to speed up end-to-end machine learning and data processing workflows.
- 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: DMLC (Distributed Machine Learning Community) Triple: [MXNet, previouslyDevelopedBy, DMLC (Distributed Machine Learning Community)]
Generated description
DMLC (Distributed Machine Learning Community) is an open-source collaborative group that develops scalable machine learning and deep learning systems and tools, including major projects like Apache MXNet and XGBoost.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DMLC (Distributed Machine Learning Community) Target entity description: DMLC (Distributed Machine Learning Community) is an open-source collaborative group that develops scalable machine learning and deep learning systems and tools, including major projects like Apache MXNet and XGBoost.
-
A.
MXNet
MXNet is an open-source deep learning framework designed for efficient, scalable training and inference across multiple GPUs and distributed systems.
-
B.
PaddlePaddle
PaddlePaddle is an open-source deep learning platform developed by Baidu, designed for large-scale distributed training and deployment of neural networks.
-
C.
Microsoft Cognitive Toolkit
Microsoft Cognitive Toolkit (CNTK) is an open-source deep learning framework developed by Microsoft for building, training, and deploying neural networks at scale.
-
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.
NVIDIA RAPIDS
NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and analytics libraries designed to speed up end-to-end machine learning and data processing workflows.
- F. None of above. chosen
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previouslyDevelopedBy Context triple: [MXNet, previouslyDevelopedBy, DMLC (Distributed Machine Learning Community)]
-
A.
formerlyDevelopedBy
chosen
Indicates that an entity was developed in the past by another entity, but is no longer developed by that same party.
-
B.
previouslyReleasedBy
Indicates that an entity was released earlier in time by a particular agent or source.
-
C.
wasLaterDevelopedBy
Indicates that something (such as an idea, product, or work) was created or further developed at a later time by a specified agent or entity.
-
D.
alsoDevelopedIn
Indicates that something was additionally developed in another context, location, or environment beyond the primary one already specified.
-
E.
isDevelopedBy
Indicates that something (such as a product, project, or idea) is created, produced, or brought into existence through the work or effort of a particular developer or group of developers.
- F. None of above.
Provenance (6 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. |
| PD | Predicate disambiguation | batch_69ccd5b5d40c8190850ad7a351445f32 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:15 p.m.