Triple

T4279774
Position Surface form Disambiguated ID Type / Status
Subject BI Engine E97119 entity
Predicate accessMethod P5872 FINISHED
Object BigQuery UI E17670 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: BigQuery UI | Statement: [BI Engine, accessMethod, BigQuery UI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BigQuery UI
Context triple: [BI Engine, accessMethod, BigQuery UI]
  • A. Google BigQuery chosen
    Google BigQuery is a fully managed, serverless cloud data warehouse from Google Cloud designed for fast SQL-based analytics on large-scale datasets.
  • B. Data Studio
    Data Studio is Google's free data visualization and business intelligence tool that lets users create interactive, shareable reports and dashboards from multiple data sources.
  • C. Business Intelligence Development Studio
    Business Intelligence Development Studio was Microsoft's former integrated development environment for creating SQL Server business intelligence solutions, including SSIS, SSAS, and SSRS projects.
  • D. Aqua Data Studio
    Aqua Data Studio is a database management and development environment that provides tools for querying, visualizing, and administering a wide range of relational and NoSQL databases.
  • E. Datalore
    Datalore is JetBrains’ collaborative data science and analytics platform that combines notebooks, computation, and team features for working with code and data in the cloud.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350367da48190b735deef9b5d2d2e completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b708b481908c1683741f84ee55 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:07 p.m.