Triple

T9926043
Position Surface form Disambiguated ID Type / Status
Subject Apache Pig E187922 entity
Predicate comparedWith P278 FINISHED
Object Apache Spark SQL E185661 NE FINISHED

How this triple was built (2 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: Apache Spark SQL | Statement: [Apache Pig, comparedWith, Apache Spark SQL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Apache Spark SQL
Context triple: [Apache Pig, comparedWith, Apache Spark SQL]
  • A. PySpark
    PySpark is the Python API for Apache Spark, enabling large-scale data processing, analysis, and machine learning using Python.
  • B. Apache Spark chosen
    Apache Spark is an open-source, distributed data processing engine designed for large-scale data analytics, machine learning, and stream processing.
  • C. 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.
  • D. Spark
    "Spark" is a 1998 piano-driven alternative rock song by Tori Amos, known for its haunting lyrics and emotional intensity.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82b22a688190b52c75bd48429c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb599e32c8190ac676fa89c131bb6 completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20e143660819097a9fa96365bc25a completed April 5, 2026, 7:24 a.m.
Created at: March 30, 2026, 8:43 p.m.