Triple
T4326282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python (via Snowpark) |
E96640
|
entity |
| Predicate | uses |
P98
|
FINISHED |
| Object |
Snowpark DataFrame API
The Snowpark DataFrame API is a developer framework for building and executing scalable, DataFrame-style data transformations and applications directly within the Snowflake data platform.
|
E431017
|
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: Snowpark DataFrame API | Statement: [Python (via Snowpark), uses, Snowpark DataFrame API]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snowpark DataFrame API Context triple: [Python (via Snowpark), uses, Snowpark DataFrame API]
-
A.
Python (via Snowpark)
Python (via Snowpark) is Snowflake’s integration of the Python language for building and running data pipelines, machine learning, and other data applications directly within the Snowflake data platform.
-
B.
pandas
pandas is a popular open-source Python library that provides powerful, easy-to-use data structures and tools for data analysis and manipulation.
-
C.
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.
-
D.
Java (via Snowpark)
Java (via Snowpark) is the capability within Snowflake’s Snowpark framework that lets developers write and execute data processing and analytics logic in Java directly inside the Snowflake data platform.
-
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: Snowpark DataFrame API Triple: [Python (via Snowpark), uses, Snowpark DataFrame API]
Generated description
The Snowpark DataFrame API is a developer framework for building and executing scalable, DataFrame-style data transformations and applications directly within the Snowflake data platform.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Snowpark DataFrame API Target entity description: The Snowpark DataFrame API is a developer framework for building and executing scalable, DataFrame-style data transformations and applications directly within the Snowflake data platform.
-
A.
Python (via Snowpark)
Python (via Snowpark) is Snowflake’s integration of the Python language for building and running data pipelines, machine learning, and other data applications directly within the Snowflake data platform.
-
B.
pandas
pandas is a popular open-source Python library that provides powerful, easy-to-use data structures and tools for data analysis and manipulation.
-
C.
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.
-
D.
Java (via Snowpark)
Java (via Snowpark) is the capability within Snowflake’s Snowpark framework that lets developers write and execute data processing and analytics logic in Java directly inside the Snowflake data platform.
-
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_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3513020f481909ff2fec3934f3002 |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d09861a4819086a88bb42a8ea2e4 |
completed | March 14, 2026, 9:18 p.m. |
| NEDg | Description generation | batch_69b5d11a30a08190b9f58fadd2415559 |
completed | March 14, 2026, 9:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5d194975481908b029ab106223c6c |
completed | March 14, 2026, 9:22 p.m. |
Created at: March 12, 2026, 11:13 p.m.