Triple

T7984565
Position Surface form Disambiguated ID Type / Status
Subject Data Analysis Expressions E185656 entity
Predicate executionEngine P9410 FINISHED
Object VertiPaq E190354 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: VertiPaq | Statement: [Data Analysis Expressions, executionEngine, VertiPaq]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: VertiPaq
Context triple: [Data Analysis Expressions, executionEngine, VertiPaq]
  • A. ColumnStore
    ColumnStore is a columnar storage engine for MariaDB designed to support scalable, high-performance analytics and data warehousing workloads.
  • B. xVelocity in-memory analytics engine chosen
    xVelocity in-memory analytics engine is a columnar, in-memory data processing engine developed by Microsoft to enable fast, compressed, and scalable analytical querying for business intelligence tools.
  • C. SAP HANA
    SAP HANA is an in-memory, column-oriented relational database management system developed by SAP for high-performance transactional and analytical processing.
  • D. Greenplum
    Greenplum is a massively parallel, open-source data warehouse and analytics platform designed for large-scale business intelligence and big data workloads.
  • E. IBM Netezza Performance Server
    IBM Netezza Performance Server is a high-performance, cloud-ready data warehouse and analytics platform designed for fast, large-scale data processing and advanced analytics workloads.
  • 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_69ca829a2cfc819083d591d58ec04075 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c2b543c81909b82bc478d579e0b completed March 31, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0e0b2748190930c22c6157d1b07 completed March 31, 2026, 2:57 p.m.
Created at: March 30, 2026, 5:15 p.m.