Triple

T825615
Position Surface form Disambiguated ID Type / Status
Subject Snowflake E17845 entity
Predicate supportsLanguage P2177 FINISHED
Object 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.
E96640 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: Python (via Snowpark) | Statement: [Snowflake, supportsLanguage, Python (via Snowpark)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Python (via Snowpark)
Context triple: [Snowflake, supportsLanguage, Python (via Snowpark)]
  • A. Azure Synapse Analytics
    Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
  • B. Power BI
    Power BI is a Microsoft business analytics and data visualization platform used to transform, analyze, and present data through interactive dashboards and reports.
  • C. pandas
    pandas is a popular open-source Python library that provides powerful, easy-to-use data structures and tools for data analysis and manipulation.
  • D. Power Query
    Power Query is a data connection and transformation tool used to import, clean, and reshape data from various sources before analysis in Microsoft Power BI and other Microsoft products.
  • E. Google BigQuery
    Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
  • 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: Python (via Snowpark)
Triple: [Snowflake, supportsLanguage, Python (via Snowpark)]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Python (via Snowpark)
Target entity description: 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.
  • A. Azure Synapse Analytics
    Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
  • B. Power BI
    Power BI is a Microsoft business analytics and data visualization platform used to transform, analyze, and present data through interactive dashboards and reports.
  • C. pandas
    pandas is a popular open-source Python library that provides powerful, easy-to-use data structures and tools for data analysis and manipulation.
  • D. Power Query
    Power Query is a data connection and transformation tool used to import, clean, and reshape data from various sources before analysis in Microsoft Power BI and other Microsoft products.
  • E. Google BigQuery
    Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
  • 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_69a4937c9c188190aaa216f6b466f452 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ab976094819086d676404d745750 completed March 1, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69a76d9577f081908aa31b1926e04bb8 completed March 3, 2026, 11:24 p.m.
NEDg Description generation batch_69a78204c1208190b2d2d19cdea93b57 completed March 4, 2026, 12:51 a.m.
NED2 Entity disambiguation (via description) batch_69a78648601881908bfcb9390ac4d6d2 completed March 4, 2026, 1:09 a.m.
Created at: March 1, 2026, 7:38 p.m.