Triple
T4276920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CuPy |
E97065
|
entity |
| Predicate | integratesWith |
P1075
|
FINISHED |
| Object |
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.
|
E426661
|
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 | Statement: [CuPy, integratesWith, Dask]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dask Context triple: [CuPy, integratesWith, Dask]
-
A.
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.
-
B.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
-
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.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
-
E.
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.
- 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 Triple: [CuPy, integratesWith, Dask]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dask Target entity description: 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.
-
A.
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.
-
B.
Apache Spark
Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
-
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.
Apache Flink
Apache Flink is an open-source distributed stream-processing framework designed for high-throughput, low-latency data processing and real-time analytics on large-scale data.
-
E.
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.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3501d677481909e7416a1d2b0008c |
completed | March 12, 2026, 11:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b7b3b52c8190ae7c05448faf5558 |
completed | March 14, 2026, 7:32 p.m. |
| NEDg | Description generation | batch_69b5b95083088190b0c993fa2fbc954c |
completed | March 14, 2026, 7:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5b9b8afcc8190822cfd560d064590 |
completed | March 14, 2026, 7:40 p.m. |
Created at: March 12, 2026, 11:07 p.m.