Triple
T4326400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowflake Data Cloud |
E96642
|
entity |
| Predicate | supportsLanguage |
P2177
|
FINISHED |
| Object |
Scala (via Snowpark)
Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
|
E431030
|
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: Scala (via Snowpark) | Statement: [Snowflake Data Cloud, supportsLanguage, Scala (via Snowpark)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scala (via Snowpark) Context triple: [Snowflake Data Cloud, supportsLanguage, Scala (via Snowpark)]
-
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.
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.
-
C.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
D.
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.
-
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: Scala (via Snowpark) Triple: [Snowflake Data Cloud, supportsLanguage, Scala (via Snowpark)]
Generated description
Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Scala (via Snowpark) Target entity description: Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
-
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.
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.
-
C.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
D.
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.
-
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.