Triple
T18178472
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BrainScript |
E435221
|
entity |
| Predicate | alternativeInterface |
P18099
|
FINISHED |
| Object | CNTK Python API |
—
|
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: CNTK Python API | Statement: [BrainScript, alternativeInterface, CNTK Python API]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CNTK Python API Context triple: [BrainScript, alternativeInterface, CNTK Python API]
-
A.
Microsoft Cognitive Toolkit
chosen
Microsoft Cognitive Toolkit (CNTK) is an open-source deep learning framework developed by Microsoft for building, training, and deploying neural networks at scale.
-
B.
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.
-
C.
Keras
Keras is a high-level neural networks API written in Python that simplifies building, training, and deploying deep learning models, often running on top of frameworks like TensorFlow.
-
D.
MXNet
MXNet is an open-source deep learning framework designed for efficient, scalable training and inference across multiple GPUs and distributed systems.
-
E.
ONNX
ONNX (Open Neural Network Exchange) is an open standard format for representing machine learning models that enables interoperability between different deep learning frameworks and tools.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternativeInterface Context triple: [BrainScript, alternativeInterface, CNTK Python API]
-
A.
relatedInterface
Indicates that one interface is associated or connected to another interface in a relevant or dependent way.
-
B.
replacedInterface
Indicates that one interface has been substituted or superseded by another interface.
-
C.
usesInterface
Indicates that one entity interacts with or operates another entity through a specified interface or set of interface methods.
-
D.
typicalInterface
Indicates that one entity serves as the standard or commonly used interface through which another entity is accessed or interacted with.
-
E.
alternativeForm
chosen
Indicates that one entity is an alternative version, variant, or representation of another entity.
- F. None of above.
Provenance (3 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_69d8b90c7ec081909b4694ccecb449c6 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df5b68f081908aac8210270f1499 |
completed | April 19, 2026, 1:57 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:31 a.m.