Triple

T7984801
Position Surface form Disambiguated ID Type / Status
Subject Apache Spark E185661 entity
Predicate component P35 FINISHED
Object Spark SQL
Spark SQL is the structured data processing module of Apache Spark that enables querying data using SQL and DataFrame/Dataset APIs for large-scale analytics.
 E185661 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: Spark SQL | Statement: [Apache Spark, component, Spark SQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Spark SQL
Context triple: [Apache Spark, component, Spark SQL]
  • A. Spark
    "Spark" is a virtuosic jazz fusion composition by Japanese pianist Hiromi Uehara, showcasing her signature blend of technical brilliance and energetic, genre-blurring style.
  • B. PySpark
    PySpark is the Python API for Apache Spark, enabling large-scale data processing, analysis, and machine learning using Python.
  • C. Apache Spark
    Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
  • D. Apache Hive
    Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
  • E. 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.
  • 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: Spark SQL
Triple: [Apache Spark, component, Spark SQL]
Generated description
Spark SQL is the structured data processing module of Apache Spark that enables querying data using SQL and DataFrame/Dataset APIs for large-scale analytics.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Spark SQL
Target entity description: Spark SQL is the structured data processing module of Apache Spark that enables querying data using SQL and DataFrame/Dataset APIs for large-scale analytics.
  • A. Spark
    "Spark" is a virtuosic jazz fusion composition by Japanese pianist Hiromi Uehara, showcasing her signature blend of technical brilliance and energetic, genre-blurring style.
  • B. PySpark
    PySpark is the Python API for Apache Spark, enabling large-scale data processing, analysis, and machine learning using Python.
  • C. Apache Spark chosen
    Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
  • D. Apache Hive
    Apache Hive is a data warehouse and SQL-like query system built on top of Hadoop for managing and analyzing large datasets stored in distributed storage.
  • E. 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.
  • F. None of above.

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_69ca829a2cfc819083d591d58ec04075 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c4a55b881909a96133e56c0dffa completed March 31, 2026, 3:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc567cfe548190bbd163a32c340bcc completed March 31, 2026, 11:19 p.m.
NEDg Description generation batch_69cc58a8f3d08190bec84dc1ba3b5b84 completed March 31, 2026, 11:28 p.m.
NED2 Entity disambiguation (via description) batch_69cc5cb2963c81908a8dfbb1f84845bc completed March 31, 2026, 11:45 p.m.
Created at: March 30, 2026, 5:15 p.m.