Triple
T10882140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NVIDIA RAPIDS |
E256948
|
entity |
| Predicate | component |
P35
|
FINISHED |
| Object |
Dask-cuDF
Dask-cuDF is a RAPIDS library that enables distributed, GPU-accelerated DataFrame processing by integrating cuDF with Dask for scalable data analytics.
|
E890460
|
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: Dask-cuDF | Statement: [NVIDIA RAPIDS, component, Dask-cuDF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dask-cuDF Context triple: [NVIDIA RAPIDS, component, Dask-cuDF]
-
A.
Dask
Dask is an open-source parallel computing library for Python that enables scalable, distributed data processing and analytics using familiar interfaces like NumPy, pandas, and scikit-learn.
-
B.
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.
-
C.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
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.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
- 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: Dask-cuDF Triple: [NVIDIA RAPIDS, component, Dask-cuDF]
Generated description
Dask-cuDF is a RAPIDS library that enables distributed, GPU-accelerated DataFrame processing by integrating cuDF with Dask for scalable data analytics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dask-cuDF Target entity description: Dask-cuDF is a RAPIDS library that enables distributed, GPU-accelerated DataFrame processing by integrating cuDF with Dask for scalable data analytics.
-
A.
Dask
Dask is an open-source parallel computing library for Python that enables scalable, distributed data processing and analytics using familiar interfaces like NumPy, pandas, and scikit-learn.
-
B.
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.
-
C.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
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.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
- 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751da559c819094c3680a9f734ee7 |
completed | April 9, 2026, 7:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7e479cc81909fb8510364d6fc0e |
completed | April 15, 2026, 8:41 p.m. |
| NEDg | Description generation | batch_69e002709d38819099c4402d30824612 |
completed | April 15, 2026, 9:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e005873ba48190b8c24c77611562fa |
completed | April 15, 2026, 9:39 p.m. |
Created at: April 8, 2026, 9:21 p.m.