Triple
T17561700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XGBoost |
E427706
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | DMLC (Distributed Machine Learning Community) projects |
—
|
NE NERFINISHED |
How this triple was built (2 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) projects | Statement: [XGBoost, partOf, DMLC (Distributed Machine Learning Community) projects]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DMLC (Distributed Machine Learning Community) projects Context triple: [XGBoost, partOf, DMLC (Distributed Machine Learning Community) projects]
-
A.
DMLC (Distributed Machine Learning Community)
chosen
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.
-
B.
MXNet
MXNet is an open-source deep learning framework designed for efficient, scalable training and inference across multiple GPUs and distributed systems.
-
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.
NVIDIA AI Workflows
NVIDIA AI Workflows are pre-built, end-to-end AI pipelines from NVIDIA that streamline the development, deployment, and scaling of AI applications across common enterprise use cases.
-
E.
TensorFlow ecosystem
The TensorFlow ecosystem is a comprehensive suite of tools, libraries, and extensions built around the TensorFlow machine learning framework to support model development, training, deployment, and visualization.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e456274c888190ac80402e391674dd |
completed | April 19, 2026, 4:12 a.m. |
Created at: April 10, 2026, 5:50 a.m.